FirstRanker Logo

FirstRanker.com - FirstRanker's Choice is a hub of Question Papers & Study Materials for B-Tech, B.E, M-Tech, MCA, M.Sc, MBBS, BDS, MBA, B.Sc, Degree, B.Sc Nursing, B-Pharmacy, D-Pharmacy, MD, Medical, Dental, Engineering students. All services of FirstRanker.com are FREE

📱

Get the MBBS Question Bank Android App

Access previous years' papers, solved question papers, notes, and more on the go!

Install From Play Store

Download MBA Marketing 3rd Semester Marketing Research Notes

Download MBA-Marketing (Master of Business Administration) 3rd Semester Marketing Research Notes

This post was last modified on 14 March 2022

--- Content provided by⁠ FirstRanker.com ---

MARKETING RESEARCH

Objective:

The objective of this chapter is to understand:

--- Content provided by⁠ FirstRanker.com ---


The meaning of Marketing Research

The difference between basic and applied research

--- Content provided by FirstRanker.com ---

The various classifications of Marketing Research
The scope of Marketing Research

The various methods of Marketing Research

--- Content provided by​ FirstRanker.com ---

Definition of Research

Research always starts with a question to which we seek an answer using

scientific methods. We define the question as a Problem.

--- Content provided by FirstRanker.com ---


Research is often described as an active, diligent, and systematic process of

inquiry aimed at discovering, interpreting and revising facts.

--- Content provided by‌ FirstRanker.com ---

The word research is derived from the French language; its literal meaning is 'to

investigate thoroughly'.

Undertaking research is basically applying scientific methods to find solution to

--- Content provided by‍ FirstRanker.com ---


a problem. It is a systematic and explorative study carried out to analyse and

apply various solutions to a defined problem.

--- Content provided by⁠ FirstRanker.com ---

Research can be classified into two broad categories:

1. Basic Research and

2. Applied Research

--- Content provided by⁠ FirstRanker.com ---


Basic research

Basic research is also called fundamental or pure research. As the name itself

--- Content provided by⁠ FirstRanker.com ---

refers, Basic Research is of basic nature which is not carried out in response to a

problem. It is more educative, towards understanding the fundamentals and aim

at expanding the knowledge base of an individual or organisation. It does not

--- Content provided by‌ FirstRanker.com ---


have any commercial potential.


Applied research

--- Content provided by⁠ FirstRanker.com ---


Applied Research on the otherhand is carried out to seek alternate solutions for a

problem at hand. Applied research is done to solve specific, practical questions;

--- Content provided by​ FirstRanker.com ---

its primary aim is not to gain knowledge. It specifies possible outcomes of each

of the alternatives and its commercial implications.

Applied research can be carried out by academic or industrial institutions. Often,

--- Content provided by‍ FirstRanker.com ---


an academic instituion such as a university will have a specific applied research

program funded by an industrial partner interested in that program. Electronics,

--- Content provided by‌ FirstRanker.com ---

informatics, computer science, process engineering and drug design are some of

the common areas of applied research.

Applied research can further be divided into:

--- Content provided by‌ FirstRanker.com ---


1. Problem-solving research: It involves research oriented towards a

crucial problem facing the organisation which may be issue specific.

--- Content provided by‍ FirstRanker.com ---

Ex: How do we improve the communication skills of our employees?

2. Problem-oriented research: The research is oriented towards a crucial

problem facing the organisation. It is undertaken inside the organisation

--- Content provided by​ FirstRanker.com ---


or by an external consultant on its behalf. This research is conceptual in

nature and newer innovative techniques of problem-solving are applied.

--- Content provided by‌ FirstRanker.com ---

Ex: How to improve the production yield from machine X using modern

techniques?

Activity 1:

--- Content provided by FirstRanker.com ---


Classify the following on the basis of basic research or aplied research:

1. Research carried out to understand the disease Typhoid.

--- Content provided by FirstRanker.com ---

2. Research carried out to understand the methods to improve the

productivity of people working on Machine X.

3. Research carried out to study the impact of absenteism on productivity.

--- Content provided by⁠ FirstRanker.com ---


4. Understanding a new software programme which has been launched.



--- Content provided by‍ FirstRanker.com ---

Defining Marketing Research:

Marketing research (also called consumer research) is a form of business

research. The field of marketing research as a statistical science was pioneered

--- Content provided by‌ FirstRanker.com ---


by Arthur Nielsen with the founding of the ACNielsen Company in 1923.

Marketing research is a systematic and objective study of problems pertaining to

--- Content provided by FirstRanker.com ---

the marketing of goods and services. It is applicable to any area of marketing.

Research is the only tool an organization has to keep in contact with its external

operating environment. In order to be proactive and change with the

--- Content provided by⁠ FirstRanker.com ---


environment simple questions need to be asked:

What are the customer needs and how are they changing? How to

--- Content provided by FirstRanker.com ---

meet these changing needs? What do the customers think about
existing products or services? What more are they looking at?

What are the competitors doing to retain customers in this

--- Content provided by⁠ FirstRanker.com ---

environment? Are their strategies exceeding or influencing
yours? What should you do to be more competitive?

How are macro and micro environmental factors influencing your

--- Content provided by​ FirstRanker.com ---

organisation? How will you react t this environment?

Authors have defined Marketing Research in many ways:

Kotler (1999) defines marketing research as systematic problem

--- Content provided by‍ FirstRanker.com ---


analysis, model-building and fact-finding for the purpose of improved
decision-making and control in the marketing of goods and services`.

The American Marketing Association (AMA, 1961) defines it as the

--- Content provided by‍ FirstRanker.com ---


systematic gathering, recording and analyzing of data relating to the
marketing of goods and services`.

Green and Tull have defined marketing research as the systematic and

--- Content provided by​ FirstRanker.com ---


objective search for and analysis of information relevant to the
identification and solution of any problem in the field of marketing.

The aim of marketing management is to satisfy the needs of the consumer.

--- Content provided by FirstRanker.com ---


Marketing research helps in achieving this. Marketing research is a systematic

and logical way of assessing ways of satisfying customer needs.

--- Content provided by‍ FirstRanker.com ---

According to all the above definitions, Marketing Research starts by stating the

problem or the issue to be investigated; indicate what kind of information is

required to resolve the problem; identify where and how to get it; specify the

--- Content provided by​ FirstRanker.com ---



methodology for analyzing the research findings; sum up the research findings

and then suggest the best solution for marketing decision making.

--- Content provided by FirstRanker.com ---


Scope of marketing research:

Marketing research can be used in:

--- Content provided by‌ FirstRanker.com ---

Product Management: One of the major scope of marketing research is

to manage the current products and new products. In product

management Marketing Research is helpful in

--- Content provided by​ FirstRanker.com ---


o Competitive Intelligence ? To understand the competitive

product stretegy.

--- Content provided by⁠ FirstRanker.com ---

o Prelaunch strategy for new products

o Test Marketing ? To monitor the performance of the brand by

launching in a select area and then taking it across the country. In

--- Content provided by​ FirstRanker.com ---


other words it is a small-scale product launch used to determine

the likely acceptance of the product when it is introduced into a

--- Content provided by⁠ FirstRanker.com ---

wider market.

o Concept testing - to test the acceptance of a concept by target

consumers.

--- Content provided by​ FirstRanker.com ---


Sales analyis: Marketing research is used to study the sales trend and

make suitable strategies when required. It is used to

--- Content provided by⁠ FirstRanker.com ---

o Assess market potential

o Estimation of demand for a product

o Market share estimation

--- Content provided by‍ FirstRanker.com ---


o Study seasonal variation for a product

o Market segmentation studies

--- Content provided by​ FirstRanker.com ---

o Estimate size of the market

o Need analysis to find out where the product fits in

Corporate Research: Marketing Research is used to analyse the

--- Content provided by‍ FirstRanker.com ---


corporate effectiveness. Some examples are:


o Assessing the image of the company

--- Content provided by‌ FirstRanker.com ---


o Knowledge of the company activities

Advertising Research: Advertising is an arena in which Marketing

--- Content provided by FirstRanker.com ---

Research is extensively used. Some scope are:

o Readership feedbacks ? Mainly carried out for newspapers and

magazines

--- Content provided by‍ FirstRanker.com ---


o Advertising Recall ? To assess the recall of telivision or other

advertising and thereby assess its effectiveness.

--- Content provided by FirstRanker.com ---

Syndicated Research: This is compiled by agencies on a regular basis

and sold to organisations on subscription basis.

All of these forms of marketing research can be classified as either problem-

--- Content provided by FirstRanker.com ---


identification research or as problem-solving research.

A similar distinction exists between exploratory research and conclusive

--- Content provided by⁠ FirstRanker.com ---

research.

Exploratory research provides insights into and comprehension of an

issue or situation. It should draw definitive conclusions only with

--- Content provided by​ FirstRanker.com ---


extreme caution.

Conclusive research draws conclusions: the results of the study can be

--- Content provided by‍ FirstRanker.com ---

generalized to the whole population.

Research can also be:

Primary Marketing Research: It is research conducted by an

--- Content provided by‍ FirstRanker.com ---


organisation for its own purpose which addresses its requirements. It is

generally expensive but is specific and objective to the organisation`s

--- Content provided by FirstRanker.com ---

requirement.

Secondary Marketing Research: This is used if the organisation is

considering extending its business into new markets or adding new

--- Content provided by‍ FirstRanker.com ---


services or product lines. This type of research is based on information

obtained from studies previously performed by government agencies,

--- Content provided by​ FirstRanker.com ---


chambers of commerce, trade associations and other organizations. This

also includes Census Bureau information.

--- Content provided by​ FirstRanker.com ---

In other terms this is research published previously and usually by

someone else. Secondary research costs less than primary research, but

seldom comes in a form that exactly meets the needs of the researcher. It

--- Content provided by​ FirstRanker.com ---


can cater to anyone who wishes to use the data.

This data can be found in local libraries or on the Web, but books and

--- Content provided by‌ FirstRanker.com ---

business publications, as well as magazines and newspapers, are also

great sources.

Hence, Primary research delivers more specific results than secondary research,

--- Content provided by‌ FirstRanker.com ---


which is an especially important while launching a new product or service. In

addition, primary research is usually based on statistical methodologies that

--- Content provided by‌ FirstRanker.com ---

involve sampling as small as 1 percent of a target market. This tiny

representative sample can give an accurate representation of a particular market.

With the advance in technology a lot of software have been developed which

--- Content provided by​ FirstRanker.com ---


help in primary market research online and offline thereby making analysis and

interpretation easier.

--- Content provided by‍ FirstRanker.com ---

The ideal way to conduct Marketing Research is to do secondary research first

and then do the primary research for the data not available form secondary

sources.

--- Content provided by‌ FirstRanker.com ---


Hence, secondary research lays the groundwork and primary research helps fill

in the gaps. By using both types of market research, organisations get a better

--- Content provided by‍ FirstRanker.com ---

picture of their market and have the information they need to make important

business decisions.

Activity 2:

--- Content provided by​ FirstRanker.com ---

List down areas in marketing where Marketing Research would be helpful:
............................................................................................................
............................................................................................................
............................................................................................................

--- Content provided by⁠ FirstRanker.com ---


Marketing Research Methods

Methodologically, marketing research uses four types of research designs,

--- Content provided by‌ FirstRanker.com ---

namely:

Qualitative marketing research ? This is generally used for

exploratory purposes. The data collected is qualitative and focuses on

--- Content provided by‌ FirstRanker.com ---

people`s opinions and attitudes towards a product or service.
The respondents are generally few in number and the findings cannot be
generalised tot eh whole population. No statistical methods are generally
applied.
Ex: Focus groups, In-depth interviews, and Projective techniques

--- Content provided by⁠ FirstRanker.com ---


Quantitative marketing research ? This is generally used to draw

conclusions for a specific problem. It tests a specific hypothesis and uses
random sampling techniques so as to infer from the sample to the

--- Content provided by‌ FirstRanker.com ---

population. It involves a large number of respondents and analysis is
carried out using statistical techniques.
Ex: Surveys and Questionnaires

Observational techniques - The researcher observes social phenomena

--- Content provided by​ FirstRanker.com ---


in their natural setting and draws conclusion from the same. The
observations can occur cross-sectionally (observations made at one
time) or longitudinally (observations occur over several time-periods)
Ex: Product-use analysis and computer cookie tracing

--- Content provided by‍ FirstRanker.com ---


Experimental techniques ? Here, the researcher creates a quasi-

artificial environment to try to control spurious factors, then manipulates
at least one of the variables to get an answer to a research

--- Content provided by‌ FirstRanker.com ---

Ex: Test marketing and Purchase laboratories

More than one research designs could be used at a time. They may start with

secondary research to get background information, then conduct a focus group

--- Content provided by FirstRanker.com ---


(qualitative research design) to explore the issues. Finally they might do a full

nation-wide survey (quantitative research design) in order to devise specific

--- Content provided by‌ FirstRanker.com ---

recommendations for the client organisation.

Difference between Market Research and Marketing Research

Generally Market Research and Marketing Research are confused to be the

--- Content provided by‍ FirstRanker.com ---


same. But there is a clear distinction between the both.

Market Research: Market Research involves researching a specific industry or

--- Content provided by‍ FirstRanker.com ---

market.

Ex: Researching the automobile industry to discover the number of competitors

and their market share.

--- Content provided by​ FirstRanker.com ---


Marketing Research: Marketing Research analyses a given marketing

opportunity or problem, defines the research and data collection methods

--- Content provided by‍ FirstRanker.com ---

required to deal with the problem or take advantage of the opportunity, through

to the implementation of the project. It is a more systematic method which aims

to discover the root cause for a specific problem within an organisation and put

--- Content provided by⁠ FirstRanker.com ---


forward solutions to that problem.

Ex: Research carried out to analyze and find solution for increasing turnover in

--- Content provided by FirstRanker.com ---

an organisation.

Summary:

The meaning of research is to investigate thoroughly. It can be divided into basic

--- Content provided by‌ FirstRanker.com ---


and applied research. Basic research is the pure research which is more

educative. Applied research is carried out to seek alternate solution for a

--- Content provided by​ FirstRanker.com ---

problem.

Applied research can further be classified as problem-solving research and

problem-oriented research depending upon the research problem at hand.

--- Content provided by⁠ FirstRanker.com ---


Marketing research is a systematic and objective study of problems pertaining to

the marketing of goods and services. It is applicable to any area of marketing.

--- Content provided by​ FirstRanker.com ---

For ex. Product management, sales, advertising research, etc.

Marketing Research can be Primary Market Research or Secondary Market

research depending on the data source used. It can be qualitative or quantitative

--- Content provided by​ FirstRanker.com ---


research depending upon the nature of the research.

Marketing Research is different from Market Research wherein the former is

--- Content provided by​ FirstRanker.com ---

oriented towards solving marketing problems and the latter is market related.

Questions:
Answer the following questions:

--- Content provided by‌ FirstRanker.com ---

1. What is Marketing Research?
2. Define Marketing Research as stated by various authors.


3. Why should you conduct Marketing Research?

--- Content provided by⁠ FirstRanker.com ---

4. Differentiate between basic research and applied research.
5. List down the scope of Marketing Research.
6. What is the difference between problem-solving research and problem-

oriented research?

--- Content provided by‌ FirstRanker.com ---


7. Give an example of situations where you will use exploratory research.
8. Enumerate the differences between primary and secondary marketing

research.

--- Content provided by FirstRanker.com ---


9. Give examples of Qualitative and Quantitative Marketing Research.
10. Is there any difference between Market Research and Marketing

Research? Explain

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---

Chapter 2

THE MARKETING RESEARCH PROCESS

Objectives:

--- Content provided by⁠ FirstRanker.com ---


To understand the Marketing Research Process.
To learn in detail about the various steps in the Marketing Research

Process

--- Content provided by​ FirstRanker.com ---


The Marketing Research Process

As we saw earlier Marketing Research is very much essential to make strategic

--- Content provided by‍ FirstRanker.com ---

decisions which are important for the growth of the organisation. It helps in

making the right decisions systematically using statistical methods.

Marketing Research reduces the uncertainty in the decision-making process and

--- Content provided by⁠ FirstRanker.com ---


increase the probability and magnitude of success if conducted in a systematic,

analytical, and objective manner. Marketing research by itself does not arrive at

--- Content provided by FirstRanker.com ---

marketing decisions, nor does it guarantee that the organization will be

successful in marketing its products. It is only a tool which helps in the decision

making process.

--- Content provided by‍ FirstRanker.com ---



The Marketing Research Process involves a number of inter-related activities

which have bearing on each other. Once the need for Marketing Research has

--- Content provided by⁠ FirstRanker.com ---


been established, broadly it involves the steps as depicted in Figure 1 below:

Define the research problem

--- Content provided by‍ FirstRanker.com ---

Determine research design

Identify data types and sources

Design data col ection forms

--- Content provided by FirstRanker.com ---


Determine sampling design and size

Collect the data

--- Content provided by FirstRanker.com ---

Analyze and interpret the data

Prepare the research report


--- Content provided by⁠ FirstRanker.com ---


Figure1: The steps in Marketing Research Process



--- Content provided by​ FirstRanker.com ---

Let us now know in detail about the various steps involved in the Marketing

Research Process.


--- Content provided by​ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---


1. Define the research problem



--- Content provided by‍ FirstRanker.com ---





The first step in Marketing is to define the research problem. A problem well

--- Content provided by‍ FirstRanker.com ---


defined is half-solved. If a problem is poorly defined, a good research design

cannot be developed.

--- Content provided by‍ FirstRanker.com ---

The decision problem faced by the organisation must be translated into a market

research problem in the form of questions. These questions must define the

information that is required to make the decision and how this information can

--- Content provided by‍ FirstRanker.com ---


be obtained. This way, the decision problem gets translated into a research

problem.

--- Content provided by​ FirstRanker.com ---

For example, a decision problem may be whether to launch a new product. The

corresponding research problem might be to assess whether the market would

accept the new product.

--- Content provided by‍ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---



In order to define the problem more precisely, an exploratory research can be

carried out. Survey of secondary data, pilot studies or experience surveys are

--- Content provided by FirstRanker.com ---


some of the popular methods.



--- Content provided by‍ FirstRanker.com ---



2. Determine research design


--- Content provided by​ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

The research design specifies the method and procedure for conducting a

particular study.

As studied already, marketing research and hence the research designs can be

--- Content provided by FirstRanker.com ---


classified into one of three categories

Exploratory research

--- Content provided by⁠ FirstRanker.com ---





Descriptive research

--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

Causal research




--- Content provided by‌ FirstRanker.com ---




This classification is based on the objective of the research. In some cases the

--- Content provided by​ FirstRanker.com ---

research will fall into one of these categories, but in other cases different phases

of the same research project will fall into different categories.


--- Content provided by‌ FirstRanker.com ---




Problems are formulated clearly in exploratory research. It aims at clarifying

--- Content provided by‍ FirstRanker.com ---

concepts, gathering explanations, gaining insight, eliminating impractical ideas,

and forming hypotheses. Exploratory research can be performed using a

literature search, surveying certain people about their experiences, focus groups,

--- Content provided by⁠ FirstRanker.com ---


and case studies. During the survey, exploratory research studies would not try

to acquire a representative sample, but rather, seek to interview those who are

--- Content provided by FirstRanker.com ---

knowledgeable and who might be able to provide insight concerning the

relationship among variables. Case studies can include contrasting situations or

benchmarking against an organization known for its excellence. Exploratory

--- Content provided by⁠ FirstRanker.com ---


research may develop hypotheses, but it does not seek to test them. Exploratory

research is characterized by its flexibility.

--- Content provided by​ FirstRanker.com ---





A descriptive study is undertaken when the researcher wants to know the

--- Content provided by FirstRanker.com ---


characteristics of certain groups such as age, sex, educational level, income,

occupation, etc. Descriptive research is more rigid than exploratory research and

--- Content provided by FirstRanker.com ---

seeks to describe users of a product, determine the proportion of the population

that uses a product, or predict future demand for a product. Descriptive research

should define questions, people surveyed, and the method of analysis prior to

--- Content provided by‍ FirstRanker.com ---


beginning data collection. In other words, the who, what, where, when, why, and

how aspects of the research should be defined. Such preparation allows one the

--- Content provided by⁠ FirstRanker.com ---

opportunity to make any required changes before the costly process of data

collection has begun.


--- Content provided by​ FirstRanker.com ---




There are two basic types of descriptive research: longitudinal studies and cross-

--- Content provided by‌ FirstRanker.com ---

sectional studies. Longitudinal studies are time series analyses that make

repeated measurements of the same individuals, thus allowing one to monitor

behavior such as brand-switching. However, longitudinal studies are not

--- Content provided by‌ FirstRanker.com ---


necessarily representative since many people may refuse to participate because

of the commitment required. Cross-sectional studies sample the population to

--- Content provided by‍ FirstRanker.com ---

make measurements at a specific point in time. A special type of cross-sectional

analysis is a cohort analysis, which tracks an aggregate of individuals who


--- Content provided by⁠ FirstRanker.com ---

experience the same event within the same time interval over time. Cohort

analyses are useful for long-term forecasting of product demand.


--- Content provided by FirstRanker.com ---


Causal research seeks to find cause and effect relationships between variables. It

accomplishes this goal through laboratory and field experiments.

--- Content provided by FirstRanker.com ---



3. Identify data types and sources


--- Content provided by​ FirstRanker.com ---




The next step is to determine the sources of data to be used. The researcher has

--- Content provided by‌ FirstRanker.com ---

to decide whether to go for primary data or secondary data. Sometimes a

combination of both is used.

Before going through the time and expense of collecting primary data, one

--- Content provided by‌ FirstRanker.com ---


should check for secondary data that previously may have been collected for

other purposes but that can be used in the immediate study. Secondary data may

--- Content provided by⁠ FirstRanker.com ---

be internal to the firm, such as sales invoices and warranty cards, or may be

external to the firm such as published data or commercially available data. The

government census is a valuable source of secondary data.

--- Content provided by​ FirstRanker.com ---






--- Content provided by FirstRanker.com ---

Secondary data has the advantage of saving time and reducing data gathering

costs. The disadvantages are that the data may not fit the problem perfectly and

that the accuracy may be more difficult to verify for secondary data than for

--- Content provided by​ FirstRanker.com ---


primary data.



--- Content provided by⁠ FirstRanker.com ---



Many a time the secondary data might have to be supplemented by primary data

originated specifically for the study at hand. Some common types of primary

--- Content provided by​ FirstRanker.com ---


data are:

Demographic and socioeconomic characteristics

--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---


Psychological and lifestyle characteristics



--- Content provided by​ FirstRanker.com ---



Attitudes and opinions


--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

Awareness and knowledge - for example, brand awareness



Intentions - for example, purchase intentions. While useful, intentions

--- Content provided by FirstRanker.com ---


are not a reliable indication of actual future behavior.

Motivation - a person's motives are more stable than his/her behavior, so

--- Content provided by⁠ FirstRanker.com ---

motive is a better predictor of future behavior than is past behavior.

Behavior


--- Content provided by FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---


Primary data can be obtained by communication or by observation.

Communication involves questioning respondents either verbally or in writing.

--- Content provided by FirstRanker.com ---

This method is versatile, since one needs to only ask for the information;

however, the response may not be accurate. Communication usually is quicker

and cheaper than observation. Observation involves the recording of actions and

--- Content provided by‌ FirstRanker.com ---


is performed by either a person or some mechanical or electronic device.

Observation is less versatile than communication since some attributes of a

--- Content provided by FirstRanker.com ---

person may not be readily observable, such as attitudes, awareness, knowledge,

intentions, and motivation. Observation also might take longer since observers

may have to wait for appropriate events to occur, though observation using

--- Content provided by‍ FirstRanker.com ---


scanner data might be quicker and more cost effective. Observation typically is

more accurate than communication.

--- Content provided by​ FirstRanker.com ---





Personal interviews have an interviewer bias that mail-in questionnaires do not

--- Content provided by​ FirstRanker.com ---


have. For example, in a personal interview the respondent's perception of the

interviewer may affect the responses.

--- Content provided by FirstRanker.com ---





4. Design data collection forms

--- Content provided by FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---



Once it has been decided to obtain primary data, the mode of collection needs to

be decided. Two methods are available for data collection:

--- Content provided by FirstRanker.com ---


1. Observational methods

2. Survey methods

--- Content provided by‌ FirstRanker.com ---

Observational methods: As the name itself suggests, the data are collected

through observation. An observer observes and records the data faithfully and

accurately. This may be suitable in case of some studies but is not useful to

--- Content provided by‍ FirstRanker.com ---


observe attitudes, opinions, motivations and other intangible states of mind.

Also in this method, the data collected is non-reactive, as it does not involve the

--- Content provided by FirstRanker.com ---

respondent.

Surveys: It is one of the most common methods of collecting data for primary

marketing research. Surveys can be:

--- Content provided by‍ FirstRanker.com ---


Personal: The information is sought through personal interviews. A

questionnaire is prepared and administered to the respondent during the

--- Content provided by‍ FirstRanker.com ---

interview. This is a detailed method of collecting information.

Telephonic: This is suitable if limited information is sought in a fixed

time frame.

--- Content provided by‌ FirstRanker.com ---


Mail: Here, the questionnaire is sent out in mail and the response is

sought. Timely response cannot be sought in this method as there is no

--- Content provided by‍ FirstRanker.com ---

control over the survey. All the people to whom the mail was sent may

not respond.

Sometimes a combination of two or more methods may be used. Whatever be

--- Content provided by​ FirstRanker.com ---


the method, a structured questionnaire is required to be used. The questionnaire

is an important tool for gathering primary data. Poorly constructed questions can

--- Content provided by⁠ FirstRanker.com ---

result in large errors and invalidate the research data, so significant effort should

be put into the questionnaire design. The questionnaire should be tested

thoroughly prior to conducting the survey.

--- Content provided by‌ FirstRanker.com ---


5. Determine sampling design and size



--- Content provided by FirstRanker.com ---





A sampling plan is a very important part of the research process. The marketing

--- Content provided by FirstRanker.com ---


researcher has to decide whether it will be a sample survey or a census.

Definitely a sample survey has its distinct merits.

--- Content provided by​ FirstRanker.com ---

The population from which the sample has to be drawn has to be well defined. A

broad choice is to be made between probability sampling and non-probability

sampling. The sample design is then chosen depending on the suitability and the

--- Content provided by‍ FirstRanker.com ---


availability of the sample frame.

The size of the sample chosen is based on statistical methods. This is well

--- Content provided by⁠ FirstRanker.com ---

defined and also reproduces the characteristics of the population. In practice,

however, this objective is never completely attained on account of the

occurrence of two types of errors ? errors due to bias in the selection and sapling

--- Content provided by FirstRanker.com ---


errors.



--- Content provided by‌ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---



6. Collect the data


--- Content provided by FirstRanker.com ---




The next step is to collect the data for which the research process has been

--- Content provided by FirstRanker.com ---

spelled out. The interviewing and the supervision of field work should be looked

into. One of the most difficult tasks is interviewing for marketing research.

Many a time the respondents may not part with crucial information unless

--- Content provided by‌ FirstRanker.com ---


approached with tact and intelligence. Supervision of field work is important to

ensure timely and proper completion of the field survey.

--- Content provided by‍ FirstRanker.com ---

If this is not carried out properly, then there results an interview error which

may be detrimental to marketing research.

7. Analyze and interpret the data

--- Content provided by‌ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

The next step is to analyze the data that has been collected from the field survey.

The raw data is transformed into the right format. First, it is edited so that errors

can be corrected or omitted. The data is then coded; this procedure converts the

--- Content provided by‍ FirstRanker.com ---


edited raw data into numbers or symbols. A codebook is created to document

how the data is coded. Finally, the data is tabulated to count the number of

--- Content provided by‍ FirstRanker.com ---

samples falling into various categories.

Simple tabulations count the occurrences of each variable independently of the

other variables. Cross tabulations, also known as contingency tables or cross

--- Content provided by​ FirstRanker.com ---


tabs, treats two or more variables simultaneously.

Cross tabulation is the most commonly utilized data analysis method in

--- Content provided by‌ FirstRanker.com ---

marketing research. Many studies take the analysis no further than cross

tabulation.

Once the tabulation is done, the following analysis can be carried out.

--- Content provided by⁠ FirstRanker.com ---


Conjoint Analysis: The conjoint analysis is a powerful technique for

determining consumer preferences for product attributes.

--- Content provided by‌ FirstRanker.com ---

Hypothesis Testing: The null hypothesis in an experiment is the

hypothesis that the independent variable has no effect on the dependent


--- Content provided by FirstRanker.com ---

variable. The null hypothesis is expressed as H0. This hypothesis is

assumed to be true unless proven otherwise. The alternative to the null

hypothesis is the hypothesis that the independent variable does have an

--- Content provided by⁠ FirstRanker.com ---


effect on the dependent variable. This hypothesis is known as the

alternative, research, or experimental hypothesis and is expressed as H1.

--- Content provided by⁠ FirstRanker.com ---

Once analysis is completed, make the marketing research conclusion. In order to

analyze whether research results are statistically significant or simply by chance,

a test of statistical significance can be run.

--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

8. Prepare the research report




--- Content provided by FirstRanker.com ---




All the research findings have to be compiled in a report to be then presented to

--- Content provided by‌ FirstRanker.com ---

the organization. The format of the marketing research report varies with the

needs of the organization. The report often contains the following sections:

Authorization letter for the research

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---

Table of Contents




--- Content provided by​ FirstRanker.com ---




List of illustrations

--- Content provided by⁠ FirstRanker.com ---





Executive summary

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

Research objectives




--- Content provided by‌ FirstRanker.com ---


Methodology



--- Content provided by‍ FirstRanker.com ---



Results


--- Content provided by‌ FirstRanker.com ---




Limitations

--- Content provided by​ FirstRanker.com ---





Conclusions and recommendations

--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

Appendices containing copies of the questionnaires, etc.




--- Content provided by‌ FirstRanker.com ---


The report has to be written with objectivity, coherence, clarity in the

presentation of the ideas and use of charts and diagrams. Sometimes, the study

--- Content provided by⁠ FirstRanker.com ---

might also throw up one or more areas where further investigation is required.

Summary:

Marketing Research reduces the uncertainty in the decision-making process and

--- Content provided by‍ FirstRanker.com ---


increase the probability and magnitude of success if conducted in a systematic,

analytical, and objective manner.

--- Content provided by⁠ FirstRanker.com ---


The Marketing Research Process involves a number of inter-related activities

which have bearing on each other. Each and every step plays an important role

--- Content provided by​ FirstRanker.com ---

in the research process.

Questions:

1. List out the various steps involved in the Marketing Research Process.

--- Content provided by​ FirstRanker.com ---

2. It is very important to define the research problem, explain.
3. Classify research designs and explain the relevance of each.
4. What are the types of data sources?
5. Enumerate the methods available for data collection
6. Is it important to determine the sample size? Explain.

--- Content provided by FirstRanker.com ---

7. How will you analyze the data collected from the research?
8. How will you prepare a research report?
9. The various steps in the Marketing Research Process are inter-related.

Explain.

--- Content provided by​ FirstRanker.com ---


10. Does the Market Research Process serve as a framework for finding

solution to the research problem at hand? Evaluate critically.

--- Content provided by​ FirstRanker.com ---



Chapter 3


--- Content provided by⁠ FirstRanker.com ---


RESEARCH DESIGN

Objective:

--- Content provided by‍ FirstRanker.com ---

To understand the meaning of Research Design.
To study about the various types of Research designs.
To understand the type of research design to use for specific problems.

The Research Design

--- Content provided by​ FirstRanker.com ---


Research design provides the glue that holds the research project together. A

design is used to structure the research, to show how all of the major parts of the

--- Content provided by FirstRanker.com ---

research project -- the samples or groups, measures, treatments or programs, and

methods of assignment -- work together to try to address the central research

questions.

--- Content provided by‌ FirstRanker.com ---





According to Green and Tull: A Research Design is the specification of methods

--- Content provided by⁠ FirstRanker.com ---


and procedures for acquiring the information needed. It is the over-all

operational pattern or framework of the project that stipulates what information

--- Content provided by‍ FirstRanker.com ---

is to be collected from which sources by what procedures.

Hence it is clear that Research design is the blueprint for research. It lays down

the methodology involved in the collection of information and arriving at

--- Content provided by FirstRanker.com ---


meaningful conclusions from the same.

There are many methods for studying and tackling a problem, but there are no

--- Content provided by​ FirstRanker.com ---

perfect methods. Many times more than one method could be used in the

research process.

There are many classifications accepted for a Research Design. One of the most

--- Content provided by‌ FirstRanker.com ---


accepted classification is grouping it under three types:

1. Exploratory

--- Content provided by​ FirstRanker.com ---

2. Descriptive and

3. Causal

This can be depicted as in figure 2 given below:

--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---

Researc

Resear h Desi

h D

--- Content provided by⁠ FirstRanker.com ---


gn



--- Content provided by​ FirstRanker.com ---

Explorato

Ex

r

--- Content provided by⁠ FirstRanker.com ---


plorato y R

y ese

--- Content provided by‍ FirstRanker.com ---

R

arch Desi

arch D

--- Content provided by​ FirstRanker.com ---


gn

Conc

--- Content provided by⁠ FirstRanker.com ---

Con lus

lu iv

s e Rese

--- Content provided by FirstRanker.com ---


e R

arch D

--- Content provided by⁠ FirstRanker.com ---

ese

esi

arch D

--- Content provided by FirstRanker.com ---


gn



--- Content provided by‌ FirstRanker.com ---



Descriptiv

ripti e Rese

--- Content provided by‌ FirstRanker.com ---


e R

arch

--- Content provided by​ FirstRanker.com ---

ese

Caus

Cau al research

--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

Cross

Cr

-Sec

--- Content provided by FirstRanker.com ---


-

tional Desi

--- Content provided by FirstRanker.com ---

tional

gn


--- Content provided by‌ FirstRanker.com ---




Longitudinal Des

--- Content provided by FirstRanker.com ---

Longitudin

i

al Des gn

--- Content provided by⁠ FirstRanker.com ---




Figure 2: Classification of Research Designs

--- Content provided by⁠ FirstRanker.com ---


Exploratory Research Design

As the term suggests, exploratory research is often conducted because a problem

--- Content provided by‍ FirstRanker.com ---

has not been clearly defined as yet, or its real scope is as yet unclear. It is a

process of discovery wherein you uncover as many ideas as possible. It allows

the researcher to familiarize him/herself with the problem or concept to be

--- Content provided by‍ FirstRanker.com ---


studied, and perhaps generate hypothesis to be tested. It expands knowledge. It

is the initial research, before more conclusive research is undertaken.

--- Content provided by​ FirstRanker.com ---

Exploratory research helps determine the best research design, data collection

method and selection of subjects.

Another common reason for conducting exploratory research is to test concepts

--- Content provided by​ FirstRanker.com ---


before they are launched in the marketplace, always a very costly endeavor. In

concept testing, consumers are provided either with a written concept or a

--- Content provided by‍ FirstRanker.com ---

prototype for a new, revised or repositioned product, service or strategy.

Exploratory research relies more on secondary data. It does not have a rigid

design as the researcher themselves are not very well versed with the subject and

--- Content provided by​ FirstRanker.com ---


are trying to gain knowledge of the same. Hence it can be quite informal, relying

on secondary research such as reviewing available literature and/or data, or

--- Content provided by​ FirstRanker.com ---

qualitative approaches such as informal discussions with consumers, employees,

management or competitors, and more formal approaches through in-depth

interviews, focus groups, projective methods, case studies or pilot studies.

--- Content provided by⁠ FirstRanker.com ---


The results of exploratory research are not usually useful for decision-making by

themselves, but they can provide significant insight into a given situation. The

--- Content provided by‌ FirstRanker.com ---

findings of this can be used to develop the research further. Points can be arrived

at which requires to apply the other methodologies.

Conclusive Research Design

--- Content provided by FirstRanker.com ---


Descriptive research is also used to generate hypotheses but generally has more

information available than in exploratory research. Descriptive research is

--- Content provided by⁠ FirstRanker.com ---


usually conducted to characterize one or more variables within a population,

particularly in relation to person, place, and time.

--- Content provided by FirstRanker.com ---

As the name indicates, conclusive research is meant to provide information that

is useful in reaching conclusions or decision-making. It is mostly quantitative in

nature, in the form of numbers that can be quantified and summarized. It relies

--- Content provided by​ FirstRanker.com ---


on both secondary data, particularly existing databases that are reanalyzed to

shed light on a different problem than the original one for which they were

--- Content provided by⁠ FirstRanker.com ---

constituted, and primary research, or data specifically gathered for the current

study.

The purpose of conclusive research is to provide a reliable or representative

--- Content provided by FirstRanker.com ---


picture of the population through the use of a valid research instrument. In the

case of formal research, it will also test hypothesis.

--- Content provided by FirstRanker.com ---

Conclusive research can be sub-divided into two categories:

1. Descriptive or statistical research, and

2. Causal research

--- Content provided by‌ FirstRanker.com ---


Descriptive Research

Descriptive research or statistical research provides data about the population or

--- Content provided by‌ FirstRanker.com ---

universe being studied. It describes the "who, what, when, where and how" of a

situation and not what caused it. Therefore, descriptive research is used when

the objective is to provide a systematic description that is as factual and accurate

--- Content provided by⁠ FirstRanker.com ---


as possible. It provides the number of times something occurs, or frequency,

lends itself to statistical calculations such as determining the average number of

--- Content provided by⁠ FirstRanker.com ---

occurrences or central tendencies.

One of its major limitations is that it cannot help determine what causes a

specific behaviour, motivation or occurrence. In other words, it cannot establish

--- Content provided by‍ FirstRanker.com ---


a causal research relationship between variables.

The two most common types of descriptive research designs are

--- Content provided by FirstRanker.com ---


1. Observation: Observation is a primary method of collecting data by

human, mechanical, electrical or electronic means. The researcher may

--- Content provided by FirstRanker.com ---

or may not have direct contact or communication with the people whose

behaviour is being recorded. Observation techniques can be part of

qualitative research as well as quantitative research techniques. The

--- Content provided by‌ FirstRanker.com ---


commonly used observation methods are:

Participant and non participant observation: This depends on whether the

--- Content provided by FirstRanker.com ---

researcher chooses to be part of the situation s/he is studying.

(e.g. studying team dynamics by being a team member would be

participant observation)

--- Content provided by​ FirstRanker.com ---


Obtrusive and unobtrusive observation: Depends on whether the subjects

being studied can detect the observation

--- Content provided by‍ FirstRanker.com ---

(e.g. hidden microphones or cameras observing behaviour)

Observation in natural or contrived settings: Observing the behaviour in

its natural setting and in a condition where the natural settings are

--- Content provided by⁠ FirstRanker.com ---


created.

Disguised and non-disguised observation: Depends on whether the

--- Content provided by FirstRanker.com ---

subjects being observed are aware that they are being studied or not. In

disguised observation, the researcher may not disclose his true identity

and pretend to be someone else to keep away the bias in the findings.

--- Content provided by​ FirstRanker.com ---


Structured and unstructured observation: This refers to guidelines or a

checklist being used for the aspects of the behaviour that are to be

--- Content provided by‌ FirstRanker.com ---

recorded; for instance, noting who starts the introductory conversation

between the group members and what specific words are used by way of

introduction.

--- Content provided by⁠ FirstRanker.com ---


Direct and indirect observation: This depends on whether the behaviour

is being observed during the time it occurs or after the occurrence, as in

--- Content provided by‍ FirstRanker.com ---


the case of TV viewing, for instance, where choice of program and

channel flicking can all be recorded for later analysis.

--- Content provided by⁠ FirstRanker.com ---

One distinct advantage of the observation technique is that it records actual

behaviour, not what people say they said/did or believe they will say/do. On the

other hand, the observation technique does not provide us with any insights into

--- Content provided by‍ FirstRanker.com ---


what the person may be thinking or what might motivate a given

behaviour/comment. This type of information can only be obtained by asking

--- Content provided by FirstRanker.com ---

people directly or indirectly.

2. Surveys: The survey technique mainly involves the collection of primary

data about subjects, usually by selecting a representative sample of the

--- Content provided by‌ FirstRanker.com ---


population or universe under study, through the use of a questionnaire. It

is a very popular since many different types of information can be

--- Content provided by⁠ FirstRanker.com ---

collected, including attitudinal, motivational, behavioral and perceptive

aspects. It allows for standardization and uniformity in the questions

asked and in the method of approaching subjects, making it easier to

--- Content provided by​ FirstRanker.com ---


compare and contrast answers by respondent group. It also ensures

higher reliability than some other techniques.

--- Content provided by⁠ FirstRanker.com ---

If properly designed and implemented, surveys can be an efficient and accurate

means of determining information about a given population. Results can be

provided relatively quickly, and depending on the sample size and methodology

--- Content provided by FirstRanker.com ---


chosen, they are relatively inexpensive. However, surveys also have a number of

disadvantages, which must be considered by the researcher in determining the

--- Content provided by⁠ FirstRanker.com ---

appropriate data collection technique.

Since in any survey, the respondent knows that s/he is being studied, the

information provided may not be valid insofar as the respondent may wish to

--- Content provided by‍ FirstRanker.com ---


impress (e.g. by attributing him/herself a higher income or education level) or

please (e.g. researcher by providing the kind of response s/he believes the

--- Content provided by⁠ FirstRanker.com ---

researcher is looking for) the researcher. This is known as response error or bias.

The willingness or ability to reply can also pose a problem. If the information

sought is considered sensitive or intrusive the respondent may hesitate to reply,

--- Content provided by‌ FirstRanker.com ---


leading to a high rate of refusal. This can be overcome by framing such

questions carefully.

--- Content provided by​ FirstRanker.com ---

There can be an interviewer error or bias as the interviewer can (inadvertently)

influence the response elicited through comments made or by stressing certain

words in the question itself. This is seen through facial expressions, body

--- Content provided by‌ FirstRanker.com ---


language or even the clothing that is worn.

Another consideration is response rate. Depending on the method chosen, the

--- Content provided by⁠ FirstRanker.com ---

length of the questionnaire, the type and/or motivation of the respondent, the

type of questions and/or subject matter, the time of day or place, and whether

respondents were informed to expect the survey or offered an incentive can all

--- Content provided by FirstRanker.com ---


influence the response rate obtained. Proper questionnaire design and question

wording can help increase response rate.

--- Content provided by‍ FirstRanker.com ---

Descriptive studies are also classified into:

1. Cross-sectional studies: It deals with a sample of elements from a given

population. Number of characteristics from the sample elements are

--- Content provided by‍ FirstRanker.com ---


collected and analyzed. It is of two types: field studies and surveys.

2. Longitudinal studies. This is based on panel data and panel methods. A

--- Content provided by⁠ FirstRanker.com ---

panel constitutes a group of respondents who are interviewed and

reinterviewed from time to time. Hence the same variable is repeatedly

measured. This helps in studying a particular behaviour over a period of

--- Content provided by⁠ FirstRanker.com ---


time.

Causal Research

--- Content provided by​ FirstRanker.com ---

Causal research is undertaken to see if there is a cause and effect relationship

between variables. In order to determine causality, it is important to hold the

variable that is assumed to cause the change in the other variable(s) constant and

--- Content provided by‍ FirstRanker.com ---


then measure the changes in the other variable(s). This type of research is very

complex and the researcher can never be completely certain that there are not

--- Content provided by‌ FirstRanker.com ---

other factors influencing the causal relationship, especially when dealing with

people`s attitudes and motivations. There are often much deeper psychological

considerations that even the respondent may not be aware of.

--- Content provided by​ FirstRanker.com ---


There are two research methods for exploring the cause and effect relationship

between variables:

--- Content provided by‌ FirstRanker.com ---

1. Experimentation or natural experimentation: This highly controlled method

allows the researcher to manipulate a specific independent variable in order to

determine what effect this manipulation would have on other dependent

--- Content provided by⁠ FirstRanker.com ---


variables. Experimentation also calls for a control group as well as an

experimentation group, and subjects would be assigned randomly to either

--- Content provided by⁠ FirstRanker.com ---

group. The researcher can further decide whether the experiment should take

place in a laboratory or in the field, i.e. the "natural" setting as opposed to an

"artificial" one. Laboratory research allows the researcher to control and/or

--- Content provided by​ FirstRanker.com ---


eliminate as many intervening variables as possible.

2. Simulation: Another way of establishing causality between variables is

--- Content provided by‍ FirstRanker.com ---

through the use of simulation.

A sophisticated set of mathematical formula are used to simulate or imitate a

real life situation. By changing one variable in the equation, it is possible to

--- Content provided by FirstRanker.com ---


determine the effect on the other variables in the equation.

For the natural experiments there are three classes of designs:

--- Content provided by⁠ FirstRanker.com ---

1. Time-series and trend designs

2. Cross-sectional designs and

3. A combination of the above two.

--- Content provided by FirstRanker.com ---


Time series and trend designs: In a time series design, data is collected from

the sample or population at successive intervals. The trend data relate to

--- Content provided by​ FirstRanker.com ---

matched samples drawn from the same population at successive intervals. It can

be of many types.


--- Content provided by FirstRanker.com ---


A simple design can be represented as below:

X

--- Content provided by FirstRanker.com ---





O

--- Content provided by FirstRanker.com ---


Where X indicates the exposure of a group to an experimental treatment and O

indicates the observation or measurement taken on the subject or group after an

--- Content provided by FirstRanker.com ---

experimental treatment. Another method also involves a control group. This can

be represented as below:

O1

--- Content provided by‍ FirstRanker.com ---


O2

O3

--- Content provided by​ FirstRanker.com ---

X

O4

O5

--- Content provided by​ FirstRanker.com ---


O6

O`1

--- Content provided by FirstRanker.com ---

O`2

O`3


--- Content provided by‍ FirstRanker.com ---


O`4

O`5

--- Content provided by​ FirstRanker.com ---

O`6



Where O`s represent measurement of the control group. This is termed as

--- Content provided by⁠ FirstRanker.com ---


multiple time-series design.

Cross-sectional designs: It studies the effect of different levels of treatments on

--- Content provided by⁠ FirstRanker.com ---

several groups at the same time. It can be represented as below:

X1


--- Content provided by FirstRanker.com ---


O1

X2

--- Content provided by​ FirstRanker.com ---



O2

X3

--- Content provided by⁠ FirstRanker.com ---




O3

--- Content provided by‌ FirstRanker.com ---

X4



O4

--- Content provided by​ FirstRanker.com ---


An example would be different kind of incentives given for the same product in

various territories. This would help in understanding the effect of varying the

--- Content provided by‍ FirstRanker.com ---

incentive on the sales performance across territories.

Combinational Design: This design combines both the time-series and cross-

sectional designs.

--- Content provided by‍ FirstRanker.com ---


This design is generally seen while measuring advertising effectiveness in a

panel. An advertisement is run and the respondents are asked if they have seen it

--- Content provided by​ FirstRanker.com ---

earlier. Those who have seen it earlier constitute the test group and those who

have not constitute the control group. The purchase made before and after the


--- Content provided by⁠ FirstRanker.com ---

advertisement by the test and the control group marks the advertising

effectiveness.

So many research designs have been listed. The one that is ultimately selected

--- Content provided by​ FirstRanker.com ---


should help in solving the problem. It should help in arriving at the desired

conclusions.

--- Content provided by FirstRanker.com ---

Summary:

A Research Design is the specification of methods and procedures for acquiring

the information needed. It is the blueprint for a research process.

--- Content provided by‍ FirstRanker.com ---


There are many classifications accepted for a Research Design. One of the most

accepted classification is grouping it under three types: Exploratory, Descriptive

--- Content provided by⁠ FirstRanker.com ---

and Causal.

An exploratory research is often conducted because a problem has not been

clearly defined as yet, or its real scope is as yet unclear. Conclusive research on

--- Content provided by​ FirstRanker.com ---


the other hand is meant to provide information that is useful in reaching

conclusions or decision-making. It is mostly quantitative in nature. A Causal

--- Content provided by​ FirstRanker.com ---

research is undertaken to see if there is a cause and effect relationship between

variables.

Causal research again can be: Time-series and trend designs, Cross-sectional

--- Content provided by FirstRanker.com ---


designs and a combination of the above two.

Questions:

--- Content provided by‍ FirstRanker.com ---

1. What is a Research Design? Explain.
2. Classify the Research Designs and define each of them.
3. Exploring helps in knowledge growth`. Explain with relevance to

Exploratory Research design.

--- Content provided by‌ FirstRanker.com ---


4. Conclusive research helps in drawing conclusions`. Explain.
5. What is descriptive Research? Classify and explain the same.
6. What are cross-sectional and longitudinal studies? Explain.
7. What is causal research? Explain the causal research methods.

--- Content provided by​ FirstRanker.com ---

8. What is Time series design? When is it used?
9. A good Research design is essential for solving a research problem.

Explain.

--- Content provided by FirstRanker.com ---


10. Are more than one research designs used to find a solution to a problem?

Critically evaluate the same.

--- Content provided by⁠ FirstRanker.com ---




Chapter 4

--- Content provided by​ FirstRanker.com ---



DATA SOURCES

Objective:

--- Content provided by⁠ FirstRanker.com ---


To understand the meaning and importance of data sources.
To read in detail about the sources of Primary data and secondary data

sources.

--- Content provided by‍ FirstRanker.com ---


To understand the relevance of these data sources while solving a

research problem.

--- Content provided by​ FirstRanker.com ---

Data sources

One of the most important components of Marketing Research is collection of

data required to solve a defined research problem. The general tendency of the

--- Content provided by⁠ FirstRanker.com ---


researcher is to organize a survey and collect the data from the field.

The most important point to be considered before this is to research the

--- Content provided by‍ FirstRanker.com ---

secondary sources and gather data already available. This gives a logical

perspective to problem solving. Only then the actual data required to be

collected from the primary survey can be well defined.

--- Content provided by‌ FirstRanker.com ---


Hence it is imperative to know the advantages and drawbacks of Secondary and

Primary data.

--- Content provided by‍ FirstRanker.com ---

Secondary Data

Secondary data is defined as the data that has been collected by individuals or

agencies for purposes other than those of the particular research study. For

--- Content provided by FirstRanker.com ---


example, if a government department has conducted a survey of, say, school

going children, then a uniform manufacturer might use this data for his research

--- Content provided by FirstRanker.com ---

purpose.


As mentioned earlier, it is ideal to undertake a marketing research study after a

--- Content provided by​ FirstRanker.com ---

prior search of secondary sources (also termed desk research). The reasons for

this are summed up below.


--- Content provided by‍ FirstRanker.com ---


conclusions and answer to solve the problem. Primary data collection
may not be required.

Secondary data is economical than collecting primary data. A thorough

--- Content provided by⁠ FirstRanker.com ---


examination of secondary sources can yield a great deal more
information than through a primary data collection exercise which needs
to be critically evaluated.

--- Content provided by⁠ FirstRanker.com ---

Searching secondary sources is much less time consuming than primary

data collection.

Secondary sources of information may at times consider a large sample

--- Content provided by FirstRanker.com ---


and hence can yield more accurate data than that primary research. This
is especially true for census information or syndicated reports by
government departments which are generally large scale. This is likely to
yield far more accurate results than custom designed surveys that are

--- Content provided by​ FirstRanker.com ---

based on relatively small sample sizes.

Secondary data can play a substantial role in the exploratory phase of the

research when the main objective is to define the research problem and

--- Content provided by‍ FirstRanker.com ---

to generate hypotheses. The assembly and analysis of secondary data
helps in better understanding of the marketing problem. This also gives
an idea about the course of action and missing links which can be got
from the primary research.

--- Content provided by‍ FirstRanker.com ---

Secondary sources are very useful to structure the sample and define the

population.

Disadvantages of secondary data:

--- Content provided by‍ FirstRanker.com ---


Even though the secondary data offers a lot of advantages; it also has its own

shortcomings. This corresponds to both the source and the quality of the data.

--- Content provided by‌ FirstRanker.com ---

The main disadvantages may be listed as follows:

The researcher has to be careful while using the units defined in the data.

It is better to study the definitions used prior to accepting the same for

--- Content provided by FirstRanker.com ---


research purpose.

For ex, the meaning of family might differ from urban and rural as it may

--- Content provided by‍ FirstRanker.com ---

consider the nuclear or the joint family system especially in India. Hence


while considering secondary data on the size of family, these definitions

--- Content provided by FirstRanker.com ---

need to be kept in mind.

It should be noted that definitions may change over time and if this is not

evaluated the conclusion derived may be wrong.

--- Content provided by⁠ FirstRanker.com ---


The errors of measurements are not generally published in secondary

sources and hence this should be considered while looking at data from
secondary sources. The solution is to try to speak to the individuals

--- Content provided by​ FirstRanker.com ---

involved in the collection of the data to obtain some guidance on the
level of accuracy of the data. This is especially crucial if the stake is high
in terms of commercial implications.

The data has to be validated for source biases as it may have been

--- Content provided by FirstRanker.com ---


prepared to appear exaggerated or otherwise. Hence it is better to go
through details of the purpose for which the data had been collected.

The reliability of published data may vary over time. Hence the data

--- Content provided by‌ FirstRanker.com ---


needs to be checked for time validity. For ex: New states have been
formulated in India. Data pertaining to population studies conducted
before the formation of the new state needs to be evaluated for its current
application.

--- Content provided by⁠ FirstRanker.com ---


Many a time the data collected may be outdated and hence it needs to be

refreshed again. This may otherwise hinder the analysis.

--- Content provided by‌ FirstRanker.com ---

All these drawbacks do exist, but still secondary data has it own merits. It is

ideal to use multiple sources of secondary data. In this way, these different

sources can be cross-checked and validated for the source of information. It is

--- Content provided by FirstRanker.com ---


better to disregard the data whenever any controversy exists.

The below flowchart (figure 3) depicts the evaluation procedure for using

--- Content provided by‌ FirstRanker.com ---

secondary data. As can be seen, the flowchart divides into two phases. The early

stages relate to the relevance of the data to the research objectives and the later

stages of the flowchart are concerned with questions about the accuracy of

--- Content provided by‌ FirstRanker.com ---


secondary data.


Is the data h

--- Content provided by FirstRanker.com ---


at

el

--- Content provided by‍ FirstRanker.com ---

e pful

pfu to a

t

--- Content provided by⁠ FirstRanker.com ---


nswer

nsw the

--- Content provided by‍ FirstRanker.com ---

h

questi

st ons of the

--- Content provided by​ FirstRanker.com ---


t

resea

--- Content provided by‍ FirstRanker.com ---

r

r

esea ch obj

--- Content provided by‌ FirstRanker.com ---


ch o ecti

bj

--- Content provided by FirstRanker.com ---

ve?

NO

ve?

--- Content provided by​ FirstRanker.com ---


ST

S OP

--- Content provided by FirstRanker.com ---

YES

Does

D

--- Content provided by​ FirstRanker.com ---


i

oes t app

--- Content provided by FirstRanker.com ---

a l

pp y to the

t

--- Content provided by⁠ FirstRanker.com ---


popu

p

--- Content provided by‍ FirstRanker.com ---

l

opu ati

at on o

--- Content provided by FirstRanker.com ---


o

f

--- Content provided by​ FirstRanker.com ---

inter

nt est a

er

--- Content provided by FirstRanker.com ---


nd t

n he titme p

--- Content provided by​ FirstRanker.com ---

m

eri

er od se

--- Content provided by‌ FirstRanker.com ---


o

l

--- Content provided by​ FirstRanker.com ---

d se ected?

NO

ected?

--- Content provided by FirstRanker.com ---


ST

S OP

--- Content provided by‌ FirstRanker.com ---

YES

Can

C

--- Content provided by‌ FirstRanker.com ---


the u

th

--- Content provided by FirstRanker.com ---

ni

n ts cl

ts c assi

--- Content provided by‍ FirstRanker.com ---


ass fifed be

ed

--- Content provided by⁠ FirstRanker.com ---

app

be

l

--- Content provided by⁠ FirstRanker.com ---


app ied or

ed

--- Content provided by‌ FirstRanker.com ---

rewor

ew ked as pe

ked

--- Content provided by‍ FirstRanker.com ---


r

as pe requ

--- Content provided by⁠ FirstRanker.com ---

e i

qu rement

em

--- Content provided by FirstRanker.com ---


?

NO

--- Content provided by‌ FirstRanker.com ---

?

ST

S OP

--- Content provided by FirstRanker.com ---


YES

Is the cost of data

--- Content provided by‌ FirstRanker.com ---

d

wor

w th acqu

--- Content provided by‍ FirstRanker.com ---


th

i

--- Content provided by⁠ FirstRanker.com ---

acqu rirng

n i

g t?

--- Content provided by⁠ FirstRanker.com ---


NO

ST

--- Content provided by‌ FirstRanker.com ---

S OP

YES

Is the data a

--- Content provided by FirstRanker.com ---


at

ccu

--- Content provided by⁠ FirstRanker.com ---

cc r

u ate an

d u

--- Content provided by‌ FirstRanker.com ---


an

nb

--- Content provided by​ FirstRanker.com ---

n i

b ased?

as

--- Content provided by​ FirstRanker.com ---


NO

ST

--- Content provided by​ FirstRanker.com ---

S OP

YES

US

--- Content provided by FirstRanker.com ---


U E

S T

--- Content provided by FirstRanker.com ---

E HE

H DA

E

--- Content provided by‌ FirstRanker.com ---


T

DA A

--- Content provided by FirstRanker.com ---



Figure 3: Evaluation of secondary data

Secondary sources of information:

--- Content provided by​ FirstRanker.com ---


Secondary sources of information can be collected from two sources: internal

sources and external sources.

--- Content provided by⁠ FirstRanker.com ---

Internal sources of secondary information:

Lot of data is available within an organization regarding day to day operations.

These data can be utilized wherever required. These include:

--- Content provided by⁠ FirstRanker.com ---


1. Sales data: Sales orders are received, invoiced and delivered. Cost of the

goods supplied is also recorded. Sales across different territories are
recorded via the reports received from the field. Most of these reports

--- Content provided by‌ FirstRanker.com ---

can be used for making marketing decisions. These resources are


generally overlooked while deciding on critical issues. Lot of
information pertaining to sales by territory, sales by customer type,

--- Content provided by⁠ FirstRanker.com ---

prices and discounts, average size of order by customer, customer type,
geographical area, average sales by sales person and sales by pack size
and pack type, etc.
This data can be used to identify the most profitable product and
customers, tracking sales trends, analysis on discounts given, scattering

--- Content provided by FirstRanker.com ---

pattern of sales orders, effect of seasonality on sales, etc.

2. Financial data: This relates to data on various costs involved in

procurement of raw materials, production of goods, distribution of

--- Content provided by⁠ FirstRanker.com ---

goods, conversion costs, labor costs, transportation cost, storage cost,
etc. With such data the efficiency of operation can be determined. It
helps in assessing the cost of production of a new product, analysis the
cost of free capacity, etc.

--- Content provided by‍ FirstRanker.com ---

3. Transportation data: A good record of the data relating to transport

operations determine which route to use, which transporter to use, cost of
effective routing patterns, etc. This helps in determining whether it
would be sensible to have your own vehicle or hire a vehicle. This

--- Content provided by​ FirstRanker.com ---

enables decision towards a trade off analysis towards a better
profitability.

4. Human Resource data: Enormous information could be collected from

--- Content provided by‌ FirstRanker.com ---

an organizational perspective from the human resource department. Data
on employee turnover, absenteeism, strength of employees could be
obtained. This would help in man power planning for the present and
future, succession planning, training and development for better
productivity, etc.

--- Content provided by​ FirstRanker.com ---


5. Storage data: This may help in calculating the direct product

profitability by calculating the rate of stock turn; stock handling costs,
assessing the efficiency of certain marketing operations and the

--- Content provided by FirstRanker.com ---

efficiency of the marketing system as a whole.

External sources of secondary information

Lot of secondary data is now available further to the discovery of World Wide

--- Content provided by FirstRanker.com ---


Web and lot of institutions looking at such analysis.

Large number of organizations provides marketing information including

--- Content provided by FirstRanker.com ---

national and local government agencies, quasi-government agencies, trade

associations, universities, research institutes, financial institutions, specialist

suppliers of secondary marketing data and professional marketing research

--- Content provided by‌ FirstRanker.com ---


enterprises. Dillon et al advise that searches of printed sources of secondary data

begin with referral texts such as directories, indexes, handbooks and guides.

--- Content provided by‌ FirstRanker.com ---

These sorts of publications rarely provide the data in which the researcher is

interested but serve in helping him/her locate potentially useful data sources.

The main sources of external secondary sources are (1) government (federal,

--- Content provided by​ FirstRanker.com ---


state and local) (2) trade associations (3) commercial services (4) national and

international institutions.

--- Content provided by⁠ FirstRanker.com ---

1. Government statistics: These may include all or some of the following:

Population census, Social surveys, family expenditure surveys,

Import/export statistics, Production statistics, and Agricultural statistics.

--- Content provided by​ FirstRanker.com ---


Some of the Indian government bodies are:

Population Statistics of Govt. of India ? Provides statistics related

--- Content provided by‍ FirstRanker.com ---

to general population of India

Central Bureau of Health Intelligence ? Provides health related

statistics

--- Content provided by‌ FirstRanker.com ---


Indian Council of medical Research ? Provides information on

research being conducted on major diseases

--- Content provided by‍ FirstRanker.com ---

Policy Reform Options Database ? Provides data on policy

reforms

Ministry of Health and Family Welfare ? Provides information

--- Content provided by‍ FirstRanker.com ---


on family welfare

Ministry of Statistics and Programme implementation ? Gives

--- Content provided by‌ FirstRanker.com ---

information on various statistical indicators of Indian economy

India Brand Equity Foundation ? Provides information on Indian

economy and Industry

--- Content provided by‍ FirstRanker.com ---


Insurance Regulatory and Development Authority ? Data on

Health Insurance in India.

--- Content provided by⁠ FirstRanker.com ---

2. Trade associations - They might produce a wide range of data. Normally

it may produce a trade directory and, perhaps, a yearbook.

3. Syndicated reports ? These are published market research reports from

--- Content provided by‌ FirstRanker.com ---


various organizations which charge for their information. These data

relate to consumer information and media information. These are

--- Content provided by‍ FirstRanker.com ---

generally prepared to cater to all interested and not to any specific


organizational requirement. Hence the relevant data is extracted from

--- Content provided by‍ FirstRanker.com ---

this.

4. National and international institutions: Economic reviews, Research

reports, journals and articles are all useful sources to contact. A lot of

--- Content provided by‌ FirstRanker.com ---


secondary data can be obtained from World Bank, WHO, International

Monetary Fund, International Fund for Agricultural Development,

--- Content provided by‌ FirstRanker.com ---

United Nations Development Programme, Food and Agriculture

Organization and International Labor Organization.

Advances in telecommunications technology have combined to allow people

--- Content provided by FirstRanker.com ---


around the world to exchange information quickly and easily. Internet has made

access to information relatively easier and quicker.

--- Content provided by​ FirstRanker.com ---

Primary Data:

Primary data collection begins when a researcher is not able to find the data

required for his research purpose from the secondary sources. Market

--- Content provided by‌ FirstRanker.com ---


researchers are interested in a variety of primary data about

demographic/socioeconomic

--- Content provided by‌ FirstRanker.com ---

characteristics,

attitudes/opinions/interests,

awareness/knowledge, intentions, motivation, and behavior.

--- Content provided by FirstRanker.com ---


There are two basic means of obtaining primary data depending on the nature of

the problem and by the availability of time and money:

--- Content provided by‌ FirstRanker.com ---

1. Observation

As the name implies, the researcher observes the situation of interest and records

the relevant facts, actions, or behaviors. Observation provides accurate data

--- Content provided by‍ FirstRanker.com ---


about what consumers do in certain situations but do not provide details of why

it happened.

--- Content provided by‌ FirstRanker.com ---

There are several methods of observation:

Structured ? unstructured observation: In structured observation, the

observer is given a set of behaviors to observe. In unstructured

--- Content provided by FirstRanker.com ---

observation, the observer is allowed to observe anything that may be


relevant to the research objective. In the first instance there may be a bias
and in the second the result may vary from observation to observation.

--- Content provided by​ FirstRanker.com ---


Disguised ? undisguised observation: In a disguised observation, the

subjects do not know that they are being observed. This is a better way to
observe as the subjects are not conscious that they are being observed

--- Content provided by⁠ FirstRanker.com ---

and behave freely. In an undisguised observation the subjects are aware
that they are being observed and tend to be cautious.

Observation under normal setting ? Laboratory setting: Normal setting

--- Content provided by FirstRanker.com ---

would be a field survey; laboratory setting would be under a fixed roof
or venue. The latter allows a prompt and economical way of collecting
data and permit the use of more objective measurements.

Direct ? Indirect Observation ? In the case of direct observation, the

--- Content provided by‌ FirstRanker.com ---


event or the behaviour of a person is observed as it occurs. In an indirect
observation, a record of a past behaviour is observed.

Human ? Mechanical Observation ? The observations are recorded

--- Content provided by‍ FirstRanker.com ---


manually in Human Observations. In Mechanical Observation, the
research is carried out through hidden cameras and audiometers; hence
there is no subjective bias.

--- Content provided by⁠ FirstRanker.com ---



2. Questionnaire

Questionnaires are data collecting instruments used to ask respondents questions

--- Content provided by‍ FirstRanker.com ---


to secure the desired information. Questionnaires may be administered by mail,

over the telephone, by computer, or in person.

--- Content provided by​ FirstRanker.com ---

The design of a questionnaire depends on whether the researcher wishes to

collect exploratory information (i.e. qualitative information for the purposes of

better understanding or the generation of hypotheses on a subject) or

--- Content provided by⁠ FirstRanker.com ---


quantitative information (to test specific hypotheses that have previously been

generated).

--- Content provided by‌ FirstRanker.com ---

The questionnaires can be classified into four types:

1. Structured ? non-disguised

2. Structured disguised

--- Content provided by​ FirstRanker.com ---


3. Non-structured - non- disguised

4. Non-structured ? disguised

--- Content provided by⁠ FirstRanker.com ---


Non-disguised are the direct questions and the object of enquiry is revealed to

the respondent. Disguised are the indirect questions where the object of enquiry

--- Content provided by‍ FirstRanker.com ---

is not revealed to the respondent. In a structured questionnaire the questions are

asked in a pre-determined order.

Formal standardised questionnaires: If the data is required to be analysed

--- Content provided by⁠ FirstRanker.com ---


statistically, a formal standardised questionnaire is designed. The points to be

remembered while designing such questionnaires are:

--- Content provided by​ FirstRanker.com ---

The questionnaire has to be framed in such a manner that each

respondent receives the same stimuli

The questionnaire has to be well-defined so that the interviewer is able to

--- Content provided by‌ FirstRanker.com ---


answer the respondent`s clarifications if necessary.

The response format must be easy to complete during the interviewing

--- Content provided by​ FirstRanker.com ---

process.

A well-designed questionnaire should primarily meet the research

objectives.

--- Content provided by‌ FirstRanker.com ---


A questionnaire should obtain the most complete and accurate

information possible.

--- Content provided by​ FirstRanker.com ---

The questionnaire should be brief and to the point and be so arranged

that the respondent remains interested throughout the interview.

Development of a questionnaire:

--- Content provided by‌ FirstRanker.com ---


The following steps are involved in the development of a questionnaire:

1. Choose and decide on the information required

--- Content provided by FirstRanker.com ---

The objective behind the survey should be kept in mind while designing a

questionnaire. Though the researcher has an idea about the kind of information

to be collected, additional help can be obtained from secondary data. In respect

--- Content provided by FirstRanker.com ---


of secondary data, the researcher should be aware of what work has been done

on the same or similar problems in the past, what factors have not yet been

--- Content provided by‌ FirstRanker.com ---

examined, and how the present survey questionnaire can build on what has

already been discovered.


--- Content provided by FirstRanker.com ---





2. Define the target respondents

--- Content provided by​ FirstRanker.com ---


The researcher must define the population that he wishes to collect the data

from. Firstly, in marketing research, researchers often have to decide whether

--- Content provided by‍ FirstRanker.com ---

they should cover only existing users of the generic product type or whether to

also include non-users. Secondly, researchers have to draw up a sampling frame.

Thirdly, in designing the questionnaire we must take into account factors such as

--- Content provided by‌ FirstRanker.com ---


the age, education, etc. of the target respondents.

3. Selection of methodology to reach the target segment

--- Content provided by​ FirstRanker.com ---

This will influence not only the questions the researcher is able to ask but the

phrasing of those questions. The main methods available in survey research are:

personal interviews, group or focus interviews, mailed questionnaires and

--- Content provided by FirstRanker.com ---


telephone interviews.

Among these, the first two are used more extensively than the second pair. The

--- Content provided by‌ FirstRanker.com ---

general rule is that the more sensitive or personal the information, the more

personal the form of data collection should be.

4. Decide on question content

--- Content provided by⁠ FirstRanker.com ---


There will be lot of temptation to use questions without critically evaluating

their contribution towards the achievement of the research objectives. Hence

--- Content provided by FirstRanker.com ---

researchers must proactively look at whether the question is really required and

if it can be used in testing one or more of the hypotheses established during the

research design.

--- Content provided by‍ FirstRanker.com ---


5. Decide on type of questions

The questions can be classified into two forms, i.e. closed and open-ended. So

--- Content provided by‌ FirstRanker.com ---

In a closed type of question, the respondent chooses between an alternative

already stated. He does not get a chance to answer in a descriptive manner.

For ex.: Do you use Brand X? Yes ________ No________.

--- Content provided by​ FirstRanker.com ---


The closed type of questioning has a number of important advantages:


It is easy for the respondent to answer. He does not have to think and

--- Content provided by‍ FirstRanker.com ---


answer.

It 'prompts' the respondent so that the respondent has to rely less on

--- Content provided by‍ FirstRanker.com ---

memory while answering a question.

Analysis is easier as responses can be easily classified
It permits categorization of the response to specify the answer categories.

--- Content provided by‍ FirstRanker.com ---

It also has some disadvantages:

It does not allow the respondent the opportunity to give a different

response to those suggested.

--- Content provided by‍ FirstRanker.com ---


They 'suggest' answers that respondents may not have considered before.

In an open-ended question the respondent is asked to give a reply to a question

--- Content provided by FirstRanker.com ---

in his/her own words. No answers are suggested. These responses are

explanatory in nature and give some insights from the respondents end.

Example: "What do you like most about this Product?"

--- Content provided by⁠ FirstRanker.com ---


Open-ended questions have a lot of advantages when used in a questionnaire:

They allow the respondent to answer in his own words, with no influence

--- Content provided by‍ FirstRanker.com ---

by any specific alternatives suggested by the interviewer.

They often reveal the issues which are most important to the respondent,

and this may reveal findings which were not originally anticipated when

--- Content provided by‍ FirstRanker.com ---


the survey was initiated.

Respondents can 'qualify' their answers or emphasize their opinions.

--- Content provided by‍ FirstRanker.com ---

The inherent problem of an open-ended question is that they must be treated

with caution as:

Respondents may find it difficult to 'articulate' their responses i.e. to

--- Content provided by⁠ FirstRanker.com ---


properly and fully explain their attitudes or motivations.


Respondents may not give a full answer simply because they may forget

--- Content provided by​ FirstRanker.com ---


to mention important points. Some respondents need prompting of the

types of answer they could give.

--- Content provided by‍ FirstRanker.com ---

Data collected is in the form of verbatim comments - it has to be coded

and reduced to manageable categories. This can be time consuming for

analysis and there are numerous opportunities for error in recording and

--- Content provided by FirstRanker.com ---


interpreting the answers given on the part of interviewers.

Respondents will tend to answer open questions in different 'dimensions'.

--- Content provided by FirstRanker.com ---

Such responses need to be probed further for clarity on response.

There are a lot of advantages of this type of questions as

The researcher can avoid the potential problems of poor memory or poor

--- Content provided by⁠ FirstRanker.com ---


articulation by then subsequently being able to prompt the respondent into

considering particular response options.

--- Content provided by FirstRanker.com ---

Recording of the responses during the interview is relatively easy.

The one disadvantage of this form of question is that it requires the researcher to

have a good prior knowledge of the subject in order to generate realistic/likely

--- Content provided by​ FirstRanker.com ---


response options before printing the questionnaire.

In many situations a questionnaire will need to incorporate all these forms of

--- Content provided by FirstRanker.com ---

question, because some forms are more appropriate for seeking particular forms

of response.

6. Putting questions into a meaningful order and format

--- Content provided by​ FirstRanker.com ---


Opening questions: Opening questions generally should be easy to answer and

not in any way threatening to the respondents. This is crucial because it is the

--- Content provided by‍ FirstRanker.com ---

respondent's first exposure to the interview and sets the tone for the nature of the

task to be performed. If they find the first question difficult to understand, or

beyond their knowledge and experience, or embarrassing in some way, or

--- Content provided by‌ FirstRanker.com ---


uninteresting they are likely to break off immediately. If, on the other hand, they


find the opening question easy and pleasant to answer, they are encouraged to

--- Content provided by‍ FirstRanker.com ---


continue.

Question flow: Questions should flow in some kind of psychological order, so

--- Content provided by​ FirstRanker.com ---

that one leads easily and naturally to the next. There could be a continuity

maintained on the flow of the questions where the response from on leads to

another. This helps in creating a sequence and the respondent`s interest is

--- Content provided by⁠ FirstRanker.com ---


maintained. Questions on one subject, or one particular aspect of a subject,

should be grouped together. Respondents may feel it disconcerting to keep

--- Content provided by‌ FirstRanker.com ---

shifting from one topic to another, or to be asked to return to some subject they

thought they gave their opinions about earlier.

Question variety: Respondents become bored quickly and restless when asked

--- Content provided by‍ FirstRanker.com ---


similar questions for half an hour or so. Hence the questions need to be carefully

keyed in to maintain the interest throughout the interview.

--- Content provided by‌ FirstRanker.com ---

7. Closing questions

By the time the respondent comes to the end of the questionnaire it is quite

natural for a respondent to become increasingly indifferent to the questionnaire.

--- Content provided by‍ FirstRanker.com ---


This is mainly due to impatience or fatigue. He might give careless answers to

the later questions. Hence such questions should be included in the earlier part

--- Content provided by‍ FirstRanker.com ---

of the questionnaire. Potentially sensitive questions should be left to the end, to

avoid respondents cutting off the interview before important information is

collected.

--- Content provided by‌ FirstRanker.com ---


8. Physical appearance of the questionnaire

The physical appearance of a questionnaire has a significant effect upon both the

--- Content provided by FirstRanker.com ---

quantity and quality of marketing data obtained. Data quality can also be

affected by the physical appearance of the questionnaire with unnecessarily

confusing layouts making it more difficult for interviewers, or respondents in the

--- Content provided by FirstRanker.com ---


case of self-completion questionnaires, to complete this task accurately.


In general it is best for a questionnaire to be as short as possible. A long

--- Content provided by​ FirstRanker.com ---


questionnaire leads to a long interview and this may lead to decreasing interest

on the part of the respondent.

--- Content provided by​ FirstRanker.com ---

Piloting the questionnaires

Piloting is very mush essential to test whether the desired responses are being

obtained for the questions. Many a time, the perception of the respondents varies

--- Content provided by⁠ FirstRanker.com ---


from those of the researcher. Hence these issues can be corrected in the initial

stage itself so that the research process is facilitated. The purpose of pretesting

--- Content provided by‍ FirstRanker.com ---

the questionnaire is to determine:

If the wordings used help in achieving the desired results
Are the questions in the right order?
Are the questions easy to understand?

--- Content provided by⁠ FirstRanker.com ---

If any questions needed to be added or deleted.
Are the instructions to interviewers are adequate?

The few respondents selected for the pilot survey should be broadly

--- Content provided by‌ FirstRanker.com ---

representative of the type of respondent to be interviewed in the main survey.

If the questionnaire has been subjected to a thorough pilot test, the research

objective is easy to achieve. This solves the difficulties that may arise later in

--- Content provided by FirstRanker.com ---


terms of invalid and inadequate responses which might lead to wastage of time

and resources.

--- Content provided by‍ FirstRanker.com ---

Summary:

One of the most important components of Marketing Research is collection of

data required to solve a defined research problem. There are two types of data

--- Content provided by‌ FirstRanker.com ---


sources: Secondary and Primary.

Secondary data is defined as the data that has been collected by individuals or

--- Content provided by‍ FirstRanker.com ---

agencies for purposes other than those of the particular research study.


Secondary data can be obtained from internal sources and external sources. It

--- Content provided by‍ FirstRanker.com ---

has to be validated before use to ensure that it suits the purpose of research.

Primary data is the data collected from the field for finding the answer to the

research problem. It can be collected by two methods: Observation and

--- Content provided by⁠ FirstRanker.com ---


Questionnaire. Designing a questionnaire is very important as it determines the

quality of response sought and analyzed for finding solutions to a research

--- Content provided by‍ FirstRanker.com ---

problem at hand.

Questions:

1. Tabulate the difference between Primary and Secondary data.

--- Content provided by FirstRanker.com ---

2. Sum up the advantages of secondary data.
3. Does secondary data have some disadvantages? Explain.
4. Give a brief description about the internal sources of secondary

information.

--- Content provided by⁠ FirstRanker.com ---


5. List out some of the sources of secondary data known to you.
6. What is primary data? How is it collected?
7. Explain the methods of observation used to collect primary data.
8. Describe the various steps involved in the development of a

--- Content provided by‌ FirstRanker.com ---


questionnaire.

9. Enumerate and tabulate the differences between open and closed

--- Content provided by‌ FirstRanker.com ---

questions.

10. Give the advantages and disadvantages of open and closed questions.


--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---



Chapter 5


--- Content provided by⁠ FirstRanker.com ---


MARKETING INFORMATION SYSTEM



--- Content provided by‍ FirstRanker.com ---

Objective:

To understand the concept of Marketing Information System or MIS.
Learn about the components of an effective MIS.
List out the types of decisions facilitated by MIS.

--- Content provided by‌ FirstRanker.com ---


Marketing Information System

There are five important functions of managers: Planning, Organizing,

--- Content provided by‌ FirstRanker.com ---

Coordinating, Deciding and Controlling.

A marketing information system (MIS) is intended to bring together a lot of data

into an understandable body of information. An MIS provides processed data

--- Content provided by‍ FirstRanker.com ---


which is suitable for decision making.

According to Kotler, an MIS is more than a system of data collection or a set of

--- Content provided by‌ FirstRanker.com ---

information technologies:

"A Marketing Information System is a continuing and interacting structure of

people, equipment and procedures to gather, sort, analyse, evaluate, and

--- Content provided by​ FirstRanker.com ---


distribute pertinent, timely and accurate information for use by marketing

decision makers to improve their marketing planning, implementation, and

--- Content provided by FirstRanker.com ---

control".

According to Smith, Brien and Stafford MIS is:

A structured, interacting complex of persons, machines and procedures

--- Content provided by‍ FirstRanker.com ---


designed to generate an orderly flow of pertinent information, collected from

both intra-and extra ? firm sources, for use as the basis for decision-making in

--- Content provided by​ FirstRanker.com ---

specified responsibility areas of marketing management.

Hence, such a system facilitates decision-making in different areas of marketing

management.

--- Content provided by​ FirstRanker.com ---


Marketing Research and Marketing Information System:

There are differences between Marketing Research and Marketing Information

--- Content provided by‍ FirstRanker.com ---

System.

Marketing Research is about seeking information from external sources. Its

main purpose is to solve the research problem. It tends to focus on past

--- Content provided by FirstRanker.com ---


information and is not computer based. It is one source of information for

Market Information System.

--- Content provided by⁠ FirstRanker.com ---

Marketing Information System handles both data from internal sources like

orders, sales, inventory levels, payables, etc and also data from external sources

like developments in the macro environment.

--- Content provided by‍ FirstRanker.com ---


Components of an effective Marketing Information System:

According to Kotler, an effective Marketing Information System has the

--- Content provided by⁠ FirstRanker.com ---

following components:

1. Internal Accounting System: Maintains data pertaining to sales,

receivables, costs, etc that are internal to the organisation.

--- Content provided by⁠ FirstRanker.com ---


2. Market Intelligence System: As the name itself implies, it speaks about

the external changes occurring in the macro environment and prepares

--- Content provided by FirstRanker.com ---

mangers to make effective strategies.

3. Marketing Research System: This undertakes studies on specific

marketing problems and provides solution to the management.

--- Content provided by FirstRanker.com ---


4. Marketing Management Science System: It mainly helps in building

models for better understanding of the marketing process.

--- Content provided by FirstRanker.com ---

The below diagram (figure 4) illustrates the major components of an MIS, the

environmental factors monitored by the system and the types of marketing

decision which the MIS seeks to help in.

--- Content provided by‍ FirstRanker.com ---





Data

--- Content provided by⁠ FirstRanker.com ---


Information

Marketing

--- Content provided by‍ FirstRanker.com ---

Internal

Marketing

Strategic

--- Content provided by‌ FirstRanker.com ---


Environment

Report

--- Content provided by​ FirstRanker.com ---

Research

Decisions

System

--- Content provided by‍ FirstRanker.com ---


System

Markets

--- Content provided by‍ FirstRanker.com ---

Channels

Control

Competitors

--- Content provided by‍ FirstRanker.com ---


Marketing

Decisions

--- Content provided by‍ FirstRanker.com ---

Marketing

Political

Intel igence

--- Content provided by‍ FirstRanker.com ---


Models

Legal

--- Content provided by‍ FirstRanker.com ---

System

Operational

Economy

--- Content provided by‍ FirstRanker.com ---


Decisions

Technology

--- Content provided by​ FirstRanker.com ---

Marketing Decisions and Communications



Figure 4: Components of an MIS

--- Content provided by‍ FirstRanker.com ---


With the help of this model all the four important constituents can be explained.

A fully fledged MIS should have the following components, the methods (and

--- Content provided by⁠ FirstRanker.com ---

technologies) of collection, storing, retrieving and processing data.

Three levels of decision making can be observed here: strategic, control (or

tactical) and operational. MIS has to support all these three decision making.

--- Content provided by​ FirstRanker.com ---


Strategic decisions are very important as they have implications on changing the

structure of an organisation. Therefore the MIS must provide precise and

--- Content provided by​ FirstRanker.com ---

accurate information.

Control decisions deal with broad policy issues.

Operational decisions concern the management of the organisation's marketing

--- Content provided by⁠ FirstRanker.com ---


mix.

MIS should help the manager in his decision making process for problem

--- Content provided by​ FirstRanker.com ---

identification, generation and evaluation of alternative courses of action, to

acquire necessary feedback on implementing his decision and help him to take

corrective action.

--- Content provided by‍ FirstRanker.com ---


Summary:

There are five important functions of managers: Planning, Organizing,

--- Content provided by‌ FirstRanker.com ---

Coordinating, Deciding and Controlling.


A marketing information system (MIS) is intended to bring together a lot of data

--- Content provided by FirstRanker.com ---

into an understandable body of information. An MIS provides processed data

which is suitable for decision making.

Three levels of decision making can be observed here: strategic, control (or

--- Content provided by​ FirstRanker.com ---


tactical) and operational. MIS has to support all these three decision making.

Questions:

--- Content provided by‌ FirstRanker.com ---

1. How is a MIS beneficial to a Manager?

2. Define MIS according to various authors.

3. What is the difference between Marketing Research and Marketing

--- Content provided by‍ FirstRanker.com ---


Information System?

4. What are the components of an effective MIS? Explain.

--- Content provided by‍ FirstRanker.com ---

5. What are the types of decision making facilitated by MIS?

References for this Unit:

1. Kotler, P., (1988) Marketing Management: Analysis Planning and

--- Content provided by⁠ FirstRanker.com ---


Control, Prentice-Hall

2. Agnilar, F., (1967) Scanning The Business Environment, Macmillan,

--- Content provided by​ FirstRanker.com ---

New York

3. Green, P.E. Tull, D.S. and Albaum G (1993) Research methods for

marketing decisions, 5th edition, Prentice Hall

--- Content provided by‌ FirstRanker.com ---


4. Joselyn, R. W. (1977) Designing the marketing research,

Petrocellis/Charter, New York

--- Content provided by‌ FirstRanker.com ---

5. Dillon, W.R., Madden, T. and Firtle, N. H., (1994) Marketing Research

in a Research Environment, 3rd edition, Irwin.

6. Sudman, S. and Bradburn, N. M. (1973), Asking Questions

--- Content provided by‌ FirstRanker.com ---

7. G. C. Beri, Marketing Research, second edition, Tata McGraw-Hill

Publishing Company Limited.

8. Wikepedia ? The free encyclopedia

--- Content provided by FirstRanker.com ---





Unit 2 Sampling

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

________________________________________________________________
_______


Objectives

--- Content provided by FirstRanker.com ---


In this section, we will introduce you to the concept of sampling, sampling
methods, sample size and sampling error. After you go through this unit, you
should be able to understand :

--- Content provided by‌ FirstRanker.com ---



the concept of sampling.


--- Content provided by⁠ FirstRanker.com ---


the differences between census and sampling.



--- Content provided by​ FirstRanker.com ---

various sampling terminologies



how an appropriate sampling design can be determined.

--- Content provided by‍ FirstRanker.com ---




sampling plan and the steps in developing it.

--- Content provided by‌ FirstRanker.com ---



various probability and non-probability sampling methods.


--- Content provided by​ FirstRanker.com ---


the concept of Random-Digit Dialing.



--- Content provided by⁠ FirstRanker.com ---

the concept of sample size and the methods of determining it.



the concept of sampling error and the types.

--- Content provided by‍ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---

In this section, we have discussed the following :




--- Content provided by‍ FirstRanker.com ---




2.1. Introduction to sampling

--- Content provided by​ FirstRanker.com ---

2.1.1. When a Census Is Appropriate



2.1.2. When a Sample Is Appropriate

--- Content provided by⁠ FirstRanker.com ---




2.2. Sampling terminology

--- Content provided by FirstRanker.com ---



2.3. Determining the Appropriate Sampling Design


--- Content provided by FirstRanker.com ---




2.

--- Content provided by FirstRanker.com ---

4. Sampling Plan

2.4.1. Steps in Developing a Sampling Plan

2.5. Sampling methods

--- Content provided by​ FirstRanker.com ---


2.5.1. Types of probability sampling designs
2.5.2. Types of non-probability sampling designs

2.6. Random-Digit Dialing (RDD)

--- Content provided by​ FirstRanker.com ---


2.7. Sample size

2.8. Sampling error

--- Content provided by‌ FirstRanker.com ---

2.9. Non-response Problems




--- Content provided by‍ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

2.1. Introduction

Sampling is an important concept that we practice in our every day life.

Sampling involves selecting a relatively small number of elements from a larger

--- Content provided by‌ FirstRanker.com ---

defined group of elements and expecting that the information gathered from the
small group will allow judgments to be made about the larger group. If all the
respondents in a population are asked to provide information, such survey is
called a census. Information obtained from a subset of the population is known
as the statistic (from sample). Researchers then attempt to make an inference

--- Content provided by FirstRanker.com ---

about the population parameter with the knowledge of the relevant sample
statistic. Sampling is often used when conducting a census is impossible or
unreasonable. When using a census, the researcher is interested in collecting
primary data about or from every member of the defined target population.

--- Content provided by FirstRanker.com ---


2.1.1. When a Census Is Appropriate

A census is appropriate if the population size itself is quite small. A

--- Content provided by‍ FirstRanker.com ---

census also is conducted if information is needed from every individual or object
in the population. For example, if the researcher is interested in determining the
number of foreign students enrolled in a university, it is necessary to get
information from all the departments in the university because of possible
variations within each department. If the cost of making an incorrect decision is

--- Content provided by‍ FirstRanker.com ---

high or if sampling errors are high, then a census may be more appropriate than
a sample.



--- Content provided by‌ FirstRanker.com ---


2.1.2. When a Sample Is Appropriate

Sampling may be useful if the population size is large and if both the

--- Content provided by‍ FirstRanker.com ---

cost and time associated with obtaining information from the population is high.
The opportunity to make a quick decision may be lost if a large population must
be surveyed. With sampling, in a given time period, more time can be spent on
each personal interview, thereby increasing the response quality. It is easy to
manage surveys of smaller samples and still exercise quality control in the

--- Content provided by‌ FirstRanker.com ---

interview process. Sampling may be sufficient in many instances. If the
population being dealt with is homogeneous, then sampling is fine. If taking a
census is not possible, then sampling is the only alternative.


--- Content provided by‌ FirstRanker.com ---

2.2. Sampling terminology

2.2.1. Population


--- Content provided by‍ FirstRanker.com ---

A population is an identifiable total group or aggregation of elements

that are of interest to the researcher and pertinent to the specified problem. A
defined target population consists of the complete group of elements that are
specifically identified for investigation according to the objectives of the

--- Content provided by‌ FirstRanker.com ---

research project.

2.2.2. Element


--- Content provided by⁠ FirstRanker.com ---

An element is a person or object from which data and information are

sought. In research, the element is a particular product or group of individuals.
Elements must be unique, countable and when added together, make up the
whole target population. Target population elements must include a particular

--- Content provided by⁠ FirstRanker.com ---

consumer product, specific group of people or specific organisations.


2.2.3. Sampling units

--- Content provided by‌ FirstRanker.com ---


Sampling units are the target population elements available for selection

during the sampling process. In a simple, single-stage sample, thee sampling
units and the population elements may be the same. But many studies involve

--- Content provided by‍ FirstRanker.com ---

complex problems that require the use of a multi-stage sampling process.

2.2.4. Sampling frame


--- Content provided by FirstRanker.com ---

It is the list of all eligible sampling units. Some common sources of

sampling frames are list of registered voters and customer lists from magazine
publishers, credit card companies and the like. There are specialized commercial
companies that are in the business of developing databases that contain names,

--- Content provided by‍ FirstRanker.com ---


addresses and telephone numbers of potential population elements. It is usually
very difficult and expensive for a researcher to
gain access to truly accurate or representative , current sampling frames. In such
situations, a researcher would have to employ an alternate method such as

--- Content provided by FirstRanker.com ---

random-digit dialing or a location survey in order to generate a sample of
prospective respondents.
The sampling frame contains the operational population from which the sample
will be drawn. In an ideal situation, the operational population, the defined
target population frame and the sampling frame are identical. In those situations

--- Content provided by​ FirstRanker.com ---

where a sampling frame contains all of the eligible sampling units of the defined
population plus additional ones,
Then it is said to have over-registration.


--- Content provided by‌ FirstRanker.com ---

But if the eligible sampling units are accidentally left out of the sampling

frame, hen the frame has an under-registration condition.

2.2.5. Sampling gap

--- Content provided by‌ FirstRanker.com ---



Both over-registration and under-registration factors create sampling

gaps. A sampling gap is the representation difference between the population

--- Content provided by​ FirstRanker.com ---

elements and sampling units in the sampling frame. A sampling gap can also be
viewed as sampling frame error and occurs when certain sample units are not
excluded or complete segments of the defined target population are not
accurately represented in the sampling frame. The larger the sampling frame
error, the greater the chance of misleading and inaccurate data results.

--- Content provided by FirstRanker.com ---


2.2.6. Sampling distribution


One important assumption that underlies sampling theory is that the

--- Content provided by‌ FirstRanker.com ---


population elements are randomly distributed. If a researcher were able to do a
census of the entire target population elements, then the probability distribution
of the population, or the relative frequencies of a population`s parameters would
depict a normal bell-shaped distribution pattern.

--- Content provided by FirstRanker.com ---



Sampling distribution is the frequency distribution of a specific sample

statistic ( sample mean or sample proportion ) from repeated random samples of

--- Content provided by‍ FirstRanker.com ---

the same size.


2.2.7. Central Limit Theorem

--- Content provided by⁠ FirstRanker.com ---



The Central Limit Theorem becomes the backbone for doing survey

research and data collection through experimental designs. The theorem states

--- Content provided by FirstRanker.com ---

that for almost all defined target populations, the sampling distribution of the
mean or the percentage value derived from a simple random sample will be


approximately normally distributed, provided that the sample size is sufficiently

--- Content provided by​ FirstRanker.com ---

large. When n` is greater than or equal to 30, the sample is a large sample.



Activity 2.1.

--- Content provided by‌ FirstRanker.com ---




Develop a population list or sampling frame for an attitude study, when the target

--- Content provided by‌ FirstRanker.com ---



population is :


--- Content provided by‌ FirstRanker.com ---


i. the students of your college.



--- Content provided by‌ FirstRanker.com ---

ii. High-income families in your residential area.
iii. Shops that sell tennis rackets in your city.



--- Content provided by⁠ FirstRanker.com ---


2.3. Determining the Appropriate Sampling Design


Selection of the most appropriate sampling design should incorporate the

--- Content provided by‍ FirstRanker.com ---


seven factors :
Research objectives


--- Content provided by​ FirstRanker.com ---

A full understanding of the overall information problem situation and the

research objectives provides the initial guidelines for determining the
appropriate sampling design. If the research objectives include the desire to
generalise the sample data results to the defined target population, then the

--- Content provided by⁠ FirstRanker.com ---

researcher must seriously consider using some type of probability sampling
method rather than a non-probability sampling method. The stage of the research
project and type of research (e.g., exploratory, descriptive, casual will influence
the researcher`s selection of sampling method.
Degree of accuracy

--- Content provided by⁠ FirstRanker.com ---



The degree of accuracy required or the researcher`s tolerance for error

may vary from project to project. If the researcher wants to make predictions or

--- Content provided by‍ FirstRanker.com ---

inferences about the true position of all members of the defined target
population, then he or she must choose some type of probability sampling
method. In contrast, if the researcher is solely trying to identify and obtain
preliminary insights into the defined target population, non-probability methods
might prove to be more appropriate.

--- Content provided by FirstRanker.com ---

Availability of resources


If the researcher`s financial and human resources are restricted, these

--- Content provided by‌ FirstRanker.com ---

limitations will certainly eliminate some of the more time-consuming, complex
probability sampling methods. Researchers who are influenced by the cost
concerns versus the value of the information will often opt for a non-probability
sampling method rather than conduct no research at all.

--- Content provided by⁠ FirstRanker.com ---

Critical factors in selecting the appropriate sampling design




--- Content provided by​ FirstRanker.com ---

__________________________________________________________________



F

--- Content provided by​ FirstRanker.com ---


ac t

or

--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---


Questions

__________________________________________________________________
Research objectives

--- Content provided by​ FirstRanker.com ---


Do the research objectives call for the use of qualitative or
quantitative research designs ?

Degree of accuracy

--- Content provided by‌ FirstRanker.com ---


Does the research call for making predictions about the
defined target population or only preliminary insights ?

Availability of resources

--- Content provided by FirstRanker.com ---


Are there budget constraints with respect to the resources that
can be allocated to the research project ?

Time frame

--- Content provided by FirstRanker.com ---


How quickly does the research project have to be completed ?

Advanced knowledge of

--- Content provided by‌ FirstRanker.com ---

Are there complete lists of the defined target population

Target population


--- Content provided by FirstRanker.com ---


elements ?

Scope of the research

--- Content provided by‌ FirstRanker.com ---

Is the research going to be international, national, regional or




--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---



Time frame


--- Content provided by​ FirstRanker.com ---

Researchers who need to meet a short deadline will be more likely to

select a simple, less time-consuming sampling method rather than a more
complex and accurate method. Researchers tend to opt for using some form of
convenience sampling to gather data necessary to test the reliability of a newly

--- Content provided by FirstRanker.com ---

developed construct or scale measurement.
Advanced knowledge of the target population


In many cases, a complete list of the population elements will not be

--- Content provided by FirstRanker.com ---


available to the researcher. A lack of adequate lists may automatically rule out
systematic random sampling, stratified random sampling, or any other type of
probability sampling method. A preliminary study may be conducted to
generate information to build a sampling frame for the study. The researcher

--- Content provided by⁠ FirstRanker.com ---

must gain a strong understanding of the key descriptor factors that make up the
true members of any target population.
Scope of the research


--- Content provided by‍ FirstRanker.com ---

Whether the scope of the research project is to be international, national,

regional, or local will influence the choice of the sampling method. The
projected geographic proximity of the defined target population elements will
influence the researcher`s ability to compile needed lists of sampling units.

--- Content provided by​ FirstRanker.com ---

When the target population elements are known or viewed to be unequally
distributed geographically, a cluster sampling method may become much more
attractive than other available methods. The broader the geographical scope of
the research project, the more extensive and complex the sampling method
becomes to ensure proper representation of the population.

--- Content provided by‍ FirstRanker.com ---

Perceived statistical analysis needs


The need for statistical projections (i.e., estimates) based on the sample

--- Content provided by​ FirstRanker.com ---

results is often a criterion. Only probability sampling techniques allow the
researcher to appropriately use statistical analysis for estimates. While statistical
analysis methods can be performed on data structures obtained from non-
probability samples of people and objects, the researcher`s ability to accurately

--- Content provided by‌ FirstRanker.com ---


generalize the results and findings to the larger defined target population is very
suspect and technically inappropriate.

2.4. Sampling Plan

--- Content provided by⁠ FirstRanker.com ---



A sampling plan is the blueprint or frame work needed to ensure that the

raw data collected are representative of the defined target population. A good

--- Content provided by‌ FirstRanker.com ---

sampling plan will include, the following steps: (1) define the target population,
(2) select the data collection method, (3) identify the sampling frames needed,
(4) select the appropriate sampling method, (5) determine necessary sample
sizes and overall contact rates, (6) create an operating plan for selecting
sampling units, and (7) execute the operational plan.

--- Content provided by‌ FirstRanker.com ---


2.4.1. Steps in Developing a Sampling Plan



--- Content provided by⁠ FirstRanker.com ---


Step 1: Define the target population



--- Content provided by FirstRanker.com ---

In any sampling pan, the first task of the researcher is to

determine and identify the complete group of people or objects that should be
investigated in the project. The target population should be given its identity by
the use of descriptors that represent the characteristics of elements that make the

--- Content provided by FirstRanker.com ---

target population`s frame. These elements become the prosperity sampling units
from which a sample will be drawn. Clear understanding of the target population
will help the researcher successfully draw a representative sample. Devoting
effort to identifying the target population usually will pay off. The following
guidelines should be considered :

--- Content provided by FirstRanker.com ---




Look to the research objectives

--- Content provided by‌ FirstRanker.com ---

If the research objectives are well thought out, the target population

definition will be clear as well. The Research objectives include the research
question, the research hypothesis and a statement of the research boundaries.
Each of these elements contributes to refining the definition of the target

--- Content provided by​ FirstRanker.com ---

population.
Consider alternatives

It is rare to find a study for which there are no alternative, reasonable,

--- Content provided by FirstRanker.com ---

target population definitions. The task is to identify and evaluate several of the
alternatives. The key point is to recognise that alternative definitions exist.
Know your market

If the research objective is to learn about the market response to some

--- Content provided by FirstRanker.com ---


element of the marketing program, it is necessary to know something about the
market. Without it, the population definition will have to be unnecessarily broad
and, therefore, will lead to an unnecessary increase in research expenses.

--- Content provided by‌ FirstRanker.com ---


Consider the appropriate sampling unit

The target population consists of sampling units. A sampling unit may

--- Content provided by‌ FirstRanker.com ---

contain people, households, or products. One task is to specify which sampling
unit is appropriate.
Specify clearly what is excluded

The specification of target population should make clear what is

--- Content provided by​ FirstRanker.com ---


excluded. For example, a study of voting intentions on certain candidates and
issues might restrict the sampling population to those of voting age and even to
those who intend to vote or to those who voted in the last election.
Don't over-define

--- Content provided by⁠ FirstRanker.com ---


The population, should be compatible with the study purpose and the

research questions; but, the research should not over-define the population.
Consider convenience

--- Content provided by⁠ FirstRanker.com ---


When there is a choice, preference should be given to populations that

are convenient to sample.

--- Content provided by​ FirstRanker.com ---

Step 2: Select the data collection method


Using the information problem definition, the data requirements, and the

--- Content provided by​ FirstRanker.com ---

established research objectives, the researcher must choose a method for
collecting the required raw data from the target population elements. Choices
include interviewing approach or a self-administered survey. The method of data
collection guides the researcher in identifying and securing the necessary
sampling frame(s) for conducting the research.

--- Content provided by FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

Steps in developing a Sampling plan




--- Content provided by‌ FirstRanker.com ---

Step 1



Define the target population

--- Content provided by​ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---



Step 2


--- Content provided by​ FirstRanker.com ---


Select the data collection method



--- Content provided by‌ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---

Step 3



Identify the sampling frame(s) needed

--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---



Step 4


--- Content provided by FirstRanker.com ---


Select the appropriate sampling method



--- Content provided by FirstRanker.com ---





Step 5

--- Content provided by‌ FirstRanker.com ---




Determine the necessary sample sizes and overall

--- Content provided by FirstRanker.com ---

contact rates




--- Content provided by​ FirstRanker.com ---




Step 6

--- Content provided by‌ FirstRanker.com ---



Create an operating plan for selecting sampling units


--- Content provided by‍ FirstRanker.com ---





Step 7

--- Content provided by‍ FirstRanker.com ---




Execute the operational plan

--- Content provided by‌ FirstRanker.com ---





Step 3: Identifying the sampling frame(s) needed

--- Content provided by‌ FirstRanker.com ---



After gaining an understanding of whom or what should be investigated,

the researcher must assemble a list of eligible sampling units. This list needs to

--- Content provided by‍ FirstRanker.com ---

contain enough information about each prospective sampling unit so that the
researcher can successfully contact them. An incomplete sampling frame
decreases the likelihood of drawing a representative sample. Sampling frame
lists can be created from a number of different sources. In creating the necessary
sampling frames, the researcher must be aware of possible conditions of over-

--- Content provided by FirstRanker.com ---

registration and under-registration of the prospective sampling units. These
conditions will create sampling gaps or sampling frame errors that decrease the
likelihood of being able to draw a representative sample.


--- Content provided by‌ FirstRanker.com ---

Creating lists

The biggest problem in simple random sampling is obtaining appropriate

lists. Lists do not exist for specialised populations. A solution for this problem is

--- Content provided by‌ FirstRanker.com ---

just to use a convenient list. When lists that do not match the population are
used, biases are introduced. Sometimes several lists are combined in the hope of
obtaining a more complete representation of the population. This approach
introduces the problem of duplication. Those appearing on several lists will have
an increased chance of being selected. Removing duplication can be expensive

--- Content provided by​ FirstRanker.com ---

and must be balanced against the bias that is introduced. Another problem with
lists is simply that of keeping them current. These lists can become outdated
quickly as people move and change jobs within an organisation.
Creating lists for telephone interviewing

--- Content provided by‌ FirstRanker.com ---

Telephone directories are used extensively as a basis for generating a

sample. The concern with the use of directories is that population members may
be omitted because they have changed residences, requested an unlisted number,
or simply do not have a telephone. The incidence of unlisted numbers is

--- Content provided by‍ FirstRanker.com ---

extensive and varies dramatically from area to area. Another approach is to buy
lists from magazines, credit-card firms, mail-order firms, or other such sources.
One problem is that each such list has its own type of biases.
Dealing with population sampling frame differences

--- Content provided by FirstRanker.com ---

When a sampling frame does not coincide with a population definition,

three types of problems arise : the subset problem, the superset problem and the
intersection problem. A subset problem occurs when the sampling frame is
smaller than the population. In other words, some of the elements in the

--- Content provided by‍ FirstRanker.com ---

population will not be present in the sampling frame. A superset problem occurs
when the sampling frame is larger than the population but contains all the
elements of the population. An intersection problem occurs when some elements
of the population are omitted from the sampling frame, and when the sampling
frame contains more elements than the population.

--- Content provided by FirstRanker.com ---

Step 4: Select the appropriate sampling method



The researcher must choose between two types of sampling

--- Content provided by⁠ FirstRanker.com ---


orientations : probability and non-probability. Using a probability sampling
method will always yield better and more accurate information about the target
population`s parameters than will any of the available non-probability sampling
methods. Probability sampling has several advantages over non-probability

--- Content provided by​ FirstRanker.com ---

sampling. First, it permits the researcher to demonstrate the sample's
representativeness. Second, it allows an explicit statement as to how much
variation is introduced, because a sample is used instead of a census of the
populations. Finally, it makes possible the more explicit identification of
possible biases.

--- Content provided by⁠ FirstRanker.com ---

Step 5: Determine necessary sample sizes and overall contact rates




--- Content provided by FirstRanker.com ---

In this step of a sampling plan, the researcher must consider how precise

the sample estimates must be and how much time and money are available to
collect the required raw data. To determine the appropriate sample size,
decisions have to be made concerning (1) the variability of the population

--- Content provided by‍ FirstRanker.com ---

characteristic under investigation, (2) the level of confidence desired in the
estimates, and (3) the degree of precision desired in estimating the population
characteristic. The researcher must decide how many completed surveys will
need to enter the data analysis activities of the overall research project.
Step 6 : Create an operating plan for selecting sampling units

--- Content provided by​ FirstRanker.com ---



In this step, the researcher wants to clearly lay out, in detail, the actual

procedures to use in containing each of the prospective respondents who were

--- Content provided by⁠ FirstRanker.com ---

drawn into the sample. All instructions should be clearly written so that
interviewers know exactly what to do and how to handle any problems in the
process of contacting prospective respondents.
Step 7 : Execute the operational plan

--- Content provided by‍ FirstRanker.com ---


In some research projects, this step is similar to actually conducting the

data collection activities. (e.g., actual calling of a prospective respondent to do a
telephone interview). The important thing in this stage is to maintain

--- Content provided by‍ FirstRanker.com ---

consistency and control.




--- Content provided by​ FirstRanker.com ---



Activity 2.2.


--- Content provided by⁠ FirstRanker.com ---


A telephone survey is planned to determine the day-after recall of several test



--- Content provided by​ FirstRanker.com ---

commercials to be run in Pondicherry. Design a sampling plan.




--- Content provided by FirstRanker.com ---



2.5. Sampling methods


--- Content provided by​ FirstRanker.com ---

There are two basic sampling designs : Probability and non-probability

sampling methods. In probability sampling, each unit in the defined target
population has a known, non-zero probability of being selected for the sample,
The actual probability of selection for each sampling unit may or may not be

--- Content provided by FirstRanker.com ---

equal depending on the type of probability sampling design used. It allows the
researcher to judge the reliability and validity of raw data collected by
calculating the probability to which the findings based on the sample would
differ from the defined target population. The results obtained by the
probability method can be generalized to the target population within a specified

--- Content provided by‍ FirstRanker.com ---

margin of error through the use of statistical methods. In non-probability
sampling, the probability of selection of each sample unit is not known.
Therefore, potential sampling error cannot be accurately known either. The
selection of sampling units is based on some type of intuitive judgments, desire
or knowledge of the researcher. The degree to which the sample nay or may not

--- Content provided by⁠ FirstRanker.com ---

be representative of the defined target population depends on the sampling


approach and how well the researcher executes and controls the selection
activities. There is always a temptation to generalize non-probability sample

--- Content provided by‌ FirstRanker.com ---

data results to the defined target population.

Comparative differences of probability and non-probability sampling methods


--- Content provided by‌ FirstRanker.com ---

________________________________________________________________


Factor

--- Content provided by‌ FirstRanker.com ---



Probability sampling


--- Content provided by​ FirstRanker.com ---


Non-probability



--- Content provided by⁠ FirstRanker.com ---

sampling

_____________________________________________________________________________


--- Content provided by​ FirstRanker.com ---

1.List of the population elements Complete list necessary

Not necessary


--- Content provided by​ FirstRanker.com ---


2. Information about the-

Each unit identified

--- Content provided by‍ FirstRanker.com ---



need detail on habits,


--- Content provided by FirstRanker.com ---


sampling units



--- Content provided by​ FirstRanker.com ---






--- Content provided by FirstRanker.com ---


activities, traits etc.



--- Content provided by​ FirstRanker.com ---

3. Sampling skill



skill required

--- Content provided by​ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

little skill required



4. Time requirement

--- Content provided by‍ FirstRanker.com ---




More time-consuming

--- Content provided by‌ FirstRanker.com ---



Less time consuming


--- Content provided by FirstRanker.com ---

5. Cost per unit sampled

Moderate to high


--- Content provided by‍ FirstRanker.com ---


Low



--- Content provided by‍ FirstRanker.com ---

6. Estimate of population -

Unbiased


--- Content provided by FirstRanker.com ---




Biased

--- Content provided by‍ FirstRanker.com ---



parameters


--- Content provided by⁠ FirstRanker.com ---




7. Sample representativeness

--- Content provided by‍ FirstRanker.com ---

Assured




--- Content provided by FirstRanker.com ---


Undeterminable

8. Accuracy and

--- Content provided by‌ FirstRanker.com ---



Computed with


--- Content provided by​ FirstRanker.com ---


Unknown

Relaiability

--- Content provided by​ FirstRanker.com ---



confidence intervals

2.5.

--- Content provided by‌ FirstRanker.com ---


1. Types of probability sampling designs

9. Measurement of sampling error Statistical measures

--- Content provided by​ FirstRanker.com ---



No true measure

Sim

--- Content provided by‍ FirstRanker.com ---


ple ran dom s ampling



--- Content provided by‌ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---


available

________________________________________________________________

--- Content provided by‍ FirstRanker.com ---


Simple Random Sampling is a probability sampling procedure which

ensures that every sampling unit making up the defined target population has a
known, equal, non-zero chance of being selected. For example, let`s say an

--- Content provided by‌ FirstRanker.com ---

instructor decided to draw a sample of 10 students (n=10), from among all the
students in a Marketing Research class that consisted of 30 students ( N=30).
The instructor could write each student`s name on a separate, identical piece of
paper and place all of the names in a jar. Each student would have an equal,
known probability of selection for a sample of a given size that could be

--- Content provided by‍ FirstRanker.com ---

expressed by the formula :




--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---



Size of sample


--- Content provided by‌ FirstRanker.com ---


Probability of selection = -----------------------------------



--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---





Size of population

--- Content provided by‌ FirstRanker.com ---




Here, each student would have a 10 /30 (or 0.33) chance of being

--- Content provided by⁠ FirstRanker.com ---

randomly selected in the drawn sample. When the defined target population
consists of a larger


Types of sampling methods

--- Content provided by⁠ FirstRanker.com ---



Samplin g Methods


--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---





Probability sampling

--- Content provided by​ FirstRanker.com ---


Non-probability



--- Content provided by‍ FirstRanker.com ---

methods

sampling methods


--- Content provided by‌ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---



Simple Random sampling


--- Content provided by‍ FirstRanker.com ---


Convenience sampling

sampling

--- Content provided by FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---



Systematic Random sampling

Judgment sampling

--- Content provided by‍ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---



Stratified Random sampling

Quota sampling

--- Content provided by​ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---


Cluster sampling

Snowball sampling

--- Content provided by​ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---


number of sampling units, a more sophisticated method would be used to
randomly draw the necessary sample. One of the procedures commonly used in
marketing research is to incorporate a printed or computer generated table of
random numbers to select the sampling units. A table of random numbers is a

--- Content provided by FirstRanker.com ---

table that lists randomly generated numbers. Many computer programs have the
ability to generate a table random numbers.



--- Content provided by‍ FirstRanker.com ---

With the marketing research students defined above as the target

population a random sample could be generated by assigning each students a
unique two-digit code ranging from 01 to 30. Then we could go to the table of
random numbers and select a starting point, which can be anywhere on the table.

--- Content provided by​ FirstRanker.com ---

Using the partial table of random numbers given below, say we select the upper-
left-hand corner of the table (31) as our starting point. We would then begin to
read down the first column (or across the first row) and select those two-digit


--- Content provided by⁠ FirstRanker.com ---

numbers that matched the numbers within the acceptable range until 10 students
had been selected. Reading down the first column, we would start with 31, then
go to 14, 49,99, 54 and so on.


--- Content provided by‍ FirstRanker.com ---

A partial table of random numbers

_________________________________________


--- Content provided by‍ FirstRanker.com ---


31 25

81 44

--- Content provided by⁠ FirstRanker.com ---

54 34

67 03

14 96

--- Content provided by⁠ FirstRanker.com ---


99 80

14 54

--- Content provided by⁠ FirstRanker.com ---

30 74

49 05

49 56

--- Content provided by⁠ FirstRanker.com ---


35 51

68 36

--- Content provided by⁠ FirstRanker.com ---

99 67

57 65

14 46

--- Content provided by FirstRanker.com ---


92 88

54 14

--- Content provided by⁠ FirstRanker.com ---

95 34

93 18

78 27

--- Content provided by⁠ FirstRanker.com ---


57 50

34 89

--- Content provided by​ FirstRanker.com ---

99 14

57 37

98 67

--- Content provided by​ FirstRanker.com ---


78 25

06 90

--- Content provided by FirstRanker.com ---

39 90

40 99

00 87

--- Content provided by⁠ FirstRanker.com ---


90 42

88 18

--- Content provided by⁠ FirstRanker.com ---

20 82

09 18

84 91

--- Content provided by FirstRanker.com ---


64 80

78 84

--- Content provided by​ FirstRanker.com ---

39 91

16 08

14 89

--- Content provided by​ FirstRanker.com ---


_________________________________________

Source : M.G.Kendall and B. Babington Smith, Table of Random Sampling Numbers,

--- Content provided by‍ FirstRanker.com ---

Tracts for Computers, 24 (Cambridge, England : Cambridge University Press, 1946), p.33.




--- Content provided by⁠ FirstRanker.com ---

Use only those random numbers that matched the numbers within the

acceptable range of 01 to 30. Numbers that fall outside the acceptable range
would be disregarded. Thus, we would select students with numbers 14, 20, 25,
05, 09, 18, 06, 16, 08, and 30. If the overall research objectives call for

--- Content provided by‍ FirstRanker.com ---

telephone interviews, drawing the necessary sample can be achieved using the
random-digit dialing (RDD) technique.

Advantages and disadvantages

--- Content provided by‌ FirstRanker.com ---


The simple random sampling technique has several advantages. The

technique is easily understood and the survey`s data results can be generalised to
the defined target population with a pre-specified margin of error e`.

--- Content provided by⁠ FirstRanker.com ---




Another advantage is that simple random samples allow the researcher to

--- Content provided by FirstRanker.com ---

gain unbiased estimates of the population`s characteristics. This method
basically guarantees that every sampling unit of the population has a known and
equal chance of being selected, no matter the actual size of the sample, resulting
in a valid representation of the
Defined target population. The disadvantage of this method is the difficulty of

--- Content provided by‌ FirstRanker.com ---

obtaining a complete, current, and accurate listing of the population elements.
Simple random sampling requires that all sampling units be identified. For this
reason, simple random sampling often works best for small populations or those
where computer-derived lists are available.

--- Content provided by⁠ FirstRanker.com ---




Activity 2.3.

--- Content provided by‍ FirstRanker.com ---



By using a standard random number table, generate random numbers for
selecting 50 samples from a population of 800 students who are doing a

--- Content provided by​ FirstRanker.com ---



course on Marketing Research under ABC University.

Systematic Random Sampling

--- Content provided by​ FirstRanker.com ---




Systematic random sampling (SYMRS) is similar to simple random

--- Content provided by​ FirstRanker.com ---

sampling but requires that the defined target population be ordered in some way,
usually in the form of a customer list, taxpayer roll, or membership roster. In
research practices, SYMRS has become a very popular alternative probability
method of drawing samples. Compared to simple random sampling, systematic
random sampling is potentially less costly because it can be done relatively

--- Content provided by​ FirstRanker.com ---

quickly. When executed properly, SYMRS can create a sample of objects or
prospective respondents that is very similar in quality to a sample drawn using
simple random sampling.


--- Content provided by⁠ FirstRanker.com ---


To employ SYMRS, the researcher must be able to secure a complete

listing of the potential sampling units that make up the defined target population.
Individual sampling units are selected according to their position using a skip

--- Content provided by​ FirstRanker.com ---

interval. The skip interval is determined by dividing the number of potential
sampling units in the defined target population by the number of units desired in
the sample. The required skip interval is calculated using the formula :


--- Content provided by FirstRanker.com ---





Skip interval = Defined target population list size

--- Content provided by‌ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

Desired sample size



For instance, if the researcher wants a sample of 100 to be drawn from a

--- Content provided by‍ FirstRanker.com ---


defined target population of 1,000, the skip interval would be 10 (ie. 1,000/100).
Once the skip interval is determined, the researcher would then randomly select
a starting point and take every 10th unit until he proceeded through the entire
target population list.

--- Content provided by​ FirstRanker.com ---




There are two important considerations when using systematic random

--- Content provided by⁠ FirstRanker.com ---

sampling. First, it is important that the natural order of the defined target
population list be unrelated to the characteristic being studied. Second, the skip
interval must not correspond to a systematic change in the target population.


--- Content provided by‍ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---




Activity 2.4.

--- Content provided by​ FirstRanker.com ---




Co

--- Content provided by FirstRanker.com ---

m

pa r e and contrast simple random sampling and systematic random sampling.

Take 10 samples from a population of all the students in your class.

--- Content provided by​ FirstRanker.com ---

Write a short report on how differently the samples came out of the two methods
and which method generated a truly representative sample of your class.



--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

Steps in drawing a Systematic Random Sample


Step 1

--- Content provided by⁠ FirstRanker.com ---


Obtain a list of potential sampling units that contains an acceptable
frame of the target population elements.


--- Content provided by FirstRanker.com ---


Step 2



--- Content provided by‍ FirstRanker.com ---

Determine the total number of sampling units making up the list of the

defined target population`s elements and the desired sample size.


--- Content provided by⁠ FirstRanker.com ---



Step 3


--- Content provided by FirstRanker.com ---


Compute the needed skip interval by dividing the number of potential

sampling units on the list by the desired sample size.

--- Content provided by‍ FirstRanker.com ---




Step 4

--- Content provided by‌ FirstRanker.com ---



Using a random number generation system, randomly determine a
starting point to sample the list of names.

--- Content provided by⁠ FirstRanker.com ---




Step 5

--- Content provided by‌ FirstRanker.com ---



Apply the skip interval to determine the remaining items to be included
in the sample.

--- Content provided by‌ FirstRanker.com ---



Advantages and disadvantages


--- Content provided by‍ FirstRanker.com ---

Systematic sampling is frequently used because, if done correctly, it is a

relatively easy way to draw a sample while ensuring randomness. The
availability of lists and the shorter time required to draw a sample makes
systematic sampling an attractive, economical methods for researchers. The

--- Content provided by FirstRanker.com ---

greatest weakness of systematic random sampling is the potential for there to be
hidden patterns in the data that are not found by the researcher. This could result
in a sample that is not truly representative of the defined target population.
Another difficulty is that the researcher must know exactly how many sampling
units make up the defined target population. In research situations in which the

--- Content provided by FirstRanker.com ---

size of the target population is extremely large or unknown, identifying the true
number of units is difficult, and even estimates may not be accurate.



--- Content provided by⁠ FirstRanker.com ---


Stratified Random Sampling


Stratified random sampling (STRS) requires the separation of the defined

--- Content provided by‌ FirstRanker.com ---


target population into different groups, called strata, and the selecting of samples
from each stratum. The goal in stratifying is to minimize the variability (or
skewness) within each stratum and maximize the differences between strata. In
some ways, STRS can be compared to segmentation of the defined target

--- Content provided by​ FirstRanker.com ---

population into smaller, more homogeneous sets of elements.


To ensure that the sample maintains the required precision of the total

--- Content provided by FirstRanker.com ---

population, representative samples must be drawn from each of the smaller
population groups. Drawing a stratified random sample involves three basic
steps:


--- Content provided by‌ FirstRanker.com ---

i. Dividing the target population into homogeneous sub-groups or

strata.

ii. Drawing random samples from each stratum.

--- Content provided by‍ FirstRanker.com ---

iii. Combining the samples from each stratum into a single sample of the

target population.


--- Content provided by FirstRanker.com ---





There are two common methods for deriving samples from the strata :

--- Content provided by‌ FirstRanker.com ---


proportionate and disproportionate. In proportionate stratified sampling, the
sample size from each stratum is depended on the stratum`s size relative to the
defined target population. Therefore, the larger strata are sampled more heavily
using proportionate stratified sampling because they make up a larger

--- Content provided by‍ FirstRanker.com ---

percentage of the target population. In disproportionate stratified sampling, the
sample size selected from each stratum is independent of that stratum`s
proportion of the total defined target population. This approach is used when
stratification of the target population produces sample sizes for sub-groups that
contradict their relative importance to the study.

--- Content provided by‍ FirstRanker.com ---



An alternative type of disproportionate stratified method is optimal

allocation. In this method, consideration is given to the relative size of the

--- Content provided by FirstRanker.com ---

stratum as well as variability within the stratum to determine the necessary
sample size of each stratum. The basic logic underlying optimal allocation is
that the greater the homogeneity of the prospective sampling units within a
particular stratum, the fewer the units that would have to be selected to the
estimate the true population parameter (0 or P) accurately for that sub- group.

--- Content provided by‍ FirstRanker.com ---


The different types of stratified sampling are :

Proportional Stratified Sampling

--- Content provided by​ FirstRanker.com ---

In this type of sampling procedure the number of objects or sampling

units chosen from each group is proportional to the number in the population.
Proportional stratified sampling can further be classified as directly proportional
and inversely proportional stratified sampling.

--- Content provided by FirstRanker.com ---


Directly Proportional Stratified Sampling

Assume that a researcher is evaluating customer satisfaction for a

--- Content provided by⁠ FirstRanker.com ---

beverage that is consumed by a total of 600 people. Among the 600 people, 400
are brand-loyal and 200 are variety-seeking. Past research indicates that the level
of customer satisfaction is related to consumer characteristics, such as being
either brand-loyal or variety-seeking. Therefore, it should be beneficial to divide
the total population of 600 consumers into two groups 400 and 200 each and

--- Content provided by​ FirstRanker.com ---

randomly sample from within each of the two groups. If a sample size of 60 is
desired, then a 10 percent directly proportional stratified sampling is employed.



--- Content provided by⁠ FirstRanker.com ---

10 Percent Directly Proportional Stratified Sample

Consumer Type

Group Size

--- Content provided by FirstRanker.com ---


Size

Brand-loyal

--- Content provided by‍ FirstRanker.com ---

400

40

Variety-seeking

--- Content provided by‌ FirstRanker.com ---


200

20

--- Content provided by​ FirstRanker.com ---

Total

600

60

--- Content provided by‍ FirstRanker.com ---





Steps in drawing a Stratified Random Sample

--- Content provided by‌ FirstRanker.com ---


Step 1


Obtain a list of potential sampling units that contains an acceptable

--- Content provided by⁠ FirstRanker.com ---

frame of the target population elements.



Step 2

--- Content provided by FirstRanker.com ---


Using some type of secondary information or past experience with the
defined target population, select a stratification factor for which the
population`s distribution is skewed and can be used to determine that
the total defined target population consists of separate subpopulations of

--- Content provided by‌ FirstRanker.com ---

elements



Step 3

--- Content provided by⁠ FirstRanker.com ---


Using the selected stratification factor, segment the defined target
population into strata consistent with each of the identified separate
subpopulations.

--- Content provided by⁠ FirstRanker.com ---



Step 4

Determine whether there is a need to apply a disproportionate or

--- Content provided by FirstRanker.com ---

optimal allocation method to the stratification process. Otherwise, use
the proportionate method and then estimate the desired sample size.



--- Content provided by FirstRanker.com ---

Step 5

Select a probability sample from each stratum.


--- Content provided by​ FirstRanker.com ---




Inversely Proportional Stratified Sampling

--- Content provided by​ FirstRanker.com ---

Assume that among the 600 consumers in the population, say 200 are

very heavy drinkers and 400 are light drinkers. If a researcher values the opinion
of the heavy drinkers more than that of the light drinkers, more people will have
to be sampled from the heavy drinkers group. In such instances, one can use an

--- Content provided by​ FirstRanker.com ---



inversely proportional stratified sampling. If a sample size of 60 is desired, a 10
percent inversely proportional stratified sampling is employed.

--- Content provided by⁠ FirstRanker.com ---



10 Percent Inversely Proportional Stratified Sample

Consumer Type

--- Content provided by⁠ FirstRanker.com ---


Group Size

Size

--- Content provided by‌ FirstRanker.com ---

Heavy Drinkers

400

40

--- Content provided by​ FirstRanker.com ---


Light Drinkers

200

--- Content provided by‌ FirstRanker.com ---

20

Total

600

--- Content provided by⁠ FirstRanker.com ---


60


In inversely proportional stratified sampling, the selection probabilities

--- Content provided by FirstRanker.com ---


are computed as follows:

Denominator = 600/200 + 600/400 = 3 + 1.5 = 4.5
Heavy Drinkers proportional sample size = 3/ 4.5 = 0.667; 0.667 x 60 =

--- Content provided by⁠ FirstRanker.com ---


40

Light Drinkers proportional sample size = 1.5/4.5 = 0.333; 0.333 x 60 =

--- Content provided by‌ FirstRanker.com ---

20

Disproportional Stratified sampling

In stratified sampling, when the sample size in each group is not

--- Content provided by FirstRanker.com ---


proportional to the respective group sizes, it is known as disproportional
stratified sampling. When multiple groups are compared and their respective
group sizes are small, a proportional stratified sampling will not yield a sample
size large enough for meaningful comparisons, and disproportional stratified

--- Content provided by⁠ FirstRanker.com ---

sampling is used. One way of selecting sample sizes within each group is to
have equal group sizes in the sample. In the example of heavy and light drinkers,
a researcher could select 30 people from each of the two groups.

In general, stratified sampling is employed in many research projects,

--- Content provided by‌ FirstRanker.com ---


because it is easy to understand and execute.

Advantages and Disadvantages

--- Content provided by‍ FirstRanker.com ---


Dividing the defined target population into homogeneous strata provides

several advantages, including:

--- Content provided by FirstRanker.com ---


i. the assurance of representativeness in the sample;



--- Content provided by‌ FirstRanker.com ---

ii. the opportunity to study each stratum and make relative comparison

between strata; and


--- Content provided by⁠ FirstRanker.com ---


iii. the ability to take estimates for the target population with the

expectation of greater precision or less error in the overall sample.

--- Content provided by‍ FirstRanker.com ---

The primary difficulty encountered with stratified sampling is determining the
basis for stratifying. It is imperative that the basis for stratifying be directly
associated with the target population`s characteristics of interest. Normally, the
larger the number of relevant strata, the more precise the results. The inclusion

--- Content provided by⁠ FirstRanker.com ---


of excess or irrelevant strata will only waste time and money without providing
meaningful results.

Cluster Sampling

--- Content provided by‍ FirstRanker.com ---



While cluster sampling is similar to stratified random sampling, it is

different in that the sampling units are divided into mutually exclusive and

--- Content provided by‌ FirstRanker.com ---

collectively exhaustive sub-populations, called clusters. Each cluster is assumed
to be representative of the heterogeneity of the target population. Examples of
possible divisions for cluster sampling include the customers who patronise a
store on a given day, the audience for a movie shown at a particular time (e.g.,
the matinee), or the invoices processed during a specific week. Once the cluster

--- Content provided by FirstRanker.com ---

has been identified, the prospective sampling units are drawn into the sample by
either using a simple random sampling method or canvassing all the elements
within the defined cluster.


--- Content provided by⁠ FirstRanker.com ---


Area sampling


A popular form of cluster sampling is area sampling. In area sampling,

--- Content provided by⁠ FirstRanker.com ---


the clusters are formed by geographic designations. Examples include cities, sub
divisions and blocks. Any geographical unit with identifiable boundaries can be
used. When using area sampling, the researcher has to additional options : the
one-step approach or the two -step approach. When deciding on using one-step

--- Content provided by FirstRanker.com ---

approach, the researcher must have enough prior information about the various
geographic clusters. By assuming that all the clusters are identical, the
researcher can focus his attention on surveying the sampling units within one
designated cluster group and then generalize the data results to the full target
population. The probability aspect of this particular sampling method is

--- Content provided by FirstRanker.com ---

executed by randomly selecting one geographic cluster and performing a census
on all the sampling units located within that selected cluster.



--- Content provided by FirstRanker.com ---

Alternatively, the researcher may execute a two-step cluster sampling

approach. First, the researcher would randomly sample a set of cluster and then
would decide on the most appropriate probability method to sample individuals
within each of the selected clusters. The two-step approach is preferable over the

--- Content provided by‌ FirstRanker.com ---

one-step approach, because there is a strong possibility that a single cluster will
not be as representative of all other clusters as the researcher thinks.

Advantages and Disadvantages

--- Content provided by​ FirstRanker.com ---


The cluster sampling method is widely used in marketing research due to

its overall cost-effectiveness and feasibility of implementation, especially in area
sampling situations. In many cases, the only reliable sampling unit frame

--- Content provided by​ FirstRanker.com ---


available to researcher is one that describes and lists clusters. These lists of
geographic regions, telephone exchanges, or blocks of residential dwellings can
normally be easily compiled. Clustering method tends to be a cost-efficient way
of sampling and collecting raw data from a defined target population.

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by FirstRanker.com ---


One primary disadvantage related to cluster sampling is the tendency for

clusters to be homogeneous. The more homogeneous the cluster, the less
precise the derived sample estimate in representing the defined target

--- Content provided by FirstRanker.com ---

population`s parameters. The actual object or people within a cluster should be
as heterogeneous as those in the target population itself. Another concern with
cluster sampling methods is the appropriateness of the designated cluster factor
used to identify the sampling units within clusters.

--- Content provided by​ FirstRanker.com ---


A comparison between the stratified sampling process and the cluster

sampling process is given in the following table :

--- Content provided by‍ FirstRanker.com ---



Stratified Sampling

Cluster Sampling

--- Content provided by‍ FirstRanker.com ---


Homogeneity within group

Homogeneity between groups

--- Content provided by‌ FirstRanker.com ---


Homogeneity between groups

Homogeneity within group

--- Content provided by‌ FirstRanker.com ---


All groups are included

Random selection of groups

--- Content provided by⁠ FirstRanker.com ---


Sampling efficiency improved by increasing Sampling efficiency improved by decreasing
accuracy at a faster rate than cost

cost at a faster rate than accuracy

--- Content provided by‌ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---




Activity. 2.5.

--- Content provided by‌ FirstRanker.com ---



Compare and contrast various probability sampling methods. Prepare a chart


--- Content provided by‌ FirstRanker.com ---


showing their relative merits and demerits.



--- Content provided by​ FirstRanker.com ---

2.5.2. Types of non-probability sampling designs
Non-probability sampling typically is used in situations such as :

i. the exploratory stages of a research project,
ii. pre-testing a questionnaire,

--- Content provided by‌ FirstRanker.com ---

iii. dealing with a homogeneous population,
iv. when a researcher lacks statistical knowledge, and
i. when operational ease is required.

Convenience Sampling

--- Content provided by FirstRanker.com ---





Convenience sampling (or accidental sampling) is a method in which

--- Content provided by‍ FirstRanker.com ---


samples are drawn at the convenience of the researcher or interviewer. The
assumptions are that the target population is homogeneous and the individuals
interviewed are similar to the overall defined target population with regard to the
characteristics being studied.

--- Content provided by‌ FirstRanker.com ---


Advantages and Disadvantages


Convenience sampling allows a large number of respondents to be

--- Content provided by​ FirstRanker.com ---


interviewed in a relatively short time. For this reason, it is commonly used in
the early stages of research. The use of convenience samples in the
development phases of constructs and scale measurements can have a seriously
negative impact on the overall reliability and validity of those measures and

--- Content provided by​ FirstRanker.com ---

instruments used to collect raw data. Another major disadvantage of
convenience samples is that the raw data and results are not generalized to the
defined target population with any measure of precision. It is not possible to
measure the representativeness of the sample, because sampling error estimates
cannot be accurately determined.

--- Content provided by⁠ FirstRanker.com ---


Judgment Sampling

In judgment sampling, (also referred to as purposive sampling),

--- Content provided by‍ FirstRanker.com ---

participants are selected according to an experienced individual`s belief that they
will meet the requirements of the study. Judgmental sampling is associated with
a variety of biases. For example, shopping center intercept interviewing can
over-sample those who shop frequently, who appear friendly, and who have
uncertainty, because the sampling frame is unknown and the sampling procedure

--- Content provided by‌ FirstRanker.com ---

is not well specified.
There are situations where judgmental sampling is useful and even advisable.

First, there are times when probability sampling is either not feasible or

--- Content provided by⁠ FirstRanker.com ---

expensive. For example, a list of sidewalk vendors might be impossible to
obtain, and a judgmental sample might be appropriate in that case.

Second, if the sample size is to be very small - say, under 10 - a

--- Content provided by‍ FirstRanker.com ---

judgmental sample usually will be more reliable and representative than a
probability sample. Suppose one or two cities of medium size are to be used to
represent 200 such cities. Then it would be appropriate to pick judgmentally two
cities that appeared to be most representative with respect to such external
criteria as demographics, media habits, and shopping characteristics.

--- Content provided by FirstRanker.com ---


Third, sometimes it is useful to obtain a deliberately biased sample. If,

for example, a product or service modification is to be evaluated, it might be
possible to identify a group that, by its very nature, should be disposed toward

--- Content provided by‌ FirstRanker.com ---

the modification.



Advantages and Disadvantages

--- Content provided by‌ FirstRanker.com ---



If the judgment of the researcher or expert is correct, then the sample

generated from judgment sampling will be much better than one generated by

--- Content provided by FirstRanker.com ---

convenience sampling. But, it is not possible to measure the representativeness
of the sample. The raw data and information collected from sampling units
generated though the judgment sampling method should be interpreted as
nothing more preliminary insights.

--- Content provided by‌ FirstRanker.com ---

Quota Sampling


The quota sampling method involves the selection of prospective

--- Content provided by‍ FirstRanker.com ---

participants according to pre-specified quota regarding either demographic
characteristics (e.g., age, race, gender, income), specific attitudes (e.g.,
satisfied/dissatisfied, liking/disliking, great/marginal/no quality), or specific
behaviours (e.g., regular/occasional/ rare customer, product user/non user). The
underlying purpose of quota sampling is to provide an assurance that pre-

--- Content provided by‌ FirstRanker.com ---

specified sub-groups of the defined target population are represented on
pertinent sampling factors that are determined by the researcher or client.
Surveys frequently use quotas that have been determined by the specific nature
of the research objectives.

--- Content provided by‍ FirstRanker.com ---


In order to meet the quotas, researcher using quota sampling sometimes

overlook the problems associated with adhering to the quotas. Assume that an
oil company is interested in finding out if women assume responsibility for

--- Content provided by‌ FirstRanker.com ---

vehicle maintenance. The company is interested in interviewing women aged
below 35 and with age equal to and above 35, as well as working women and
nonworking women. Suppose the distribution of the population of women in a
city (N=1,000) is as follows:

--- Content provided by​ FirstRanker.com ---

Population Characteristics


<35 years

--- Content provided by‌ FirstRanker.com ---

35 years and Above

Total

Percentage

--- Content provided by FirstRanker.com ---


Working women

300

--- Content provided by⁠ FirstRanker.com ---

200

500

50

--- Content provided by​ FirstRanker.com ---


Non-working women

200

--- Content provided by‍ FirstRanker.com ---

300

500

50

--- Content provided by‍ FirstRanker.com ---


Total

500

--- Content provided by‌ FirstRanker.com ---

500

1,000

100

--- Content provided by​ FirstRanker.com ---


Percentage

50

--- Content provided by‌ FirstRanker.com ---

50

100


--- Content provided by‌ FirstRanker.com ---



Assume that the researcher is interested in interviewing 100 women from

this city and develops a quota system such that 50 percent of the sample should

--- Content provided by‌ FirstRanker.com ---

be working women and 50 percent of the sample should also be under 35 years
old. A quota matrix can be developed for a sample size of 100.

Sample Characteristics

--- Content provided by FirstRanker.com ---


<35 years

35 years and Above

--- Content provided by‌ FirstRanker.com ---

Total

Percentage


--- Content provided by⁠ FirstRanker.com ---

Working women

50

0

--- Content provided by‍ FirstRanker.com ---


50

50

--- Content provided by​ FirstRanker.com ---

Non-working women

0

50

--- Content provided by⁠ FirstRanker.com ---


50

50

--- Content provided by‍ FirstRanker.com ---

Total

50

50

--- Content provided by​ FirstRanker.com ---


100

100

--- Content provided by​ FirstRanker.com ---

Percentage

50

50

--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---



Advantages and Disadvantages


--- Content provided by‍ FirstRanker.com ---

The greatest advantage of quota sampling is that the sample generated

contains specific sub-groups in the proportions desired by researchers. In those
research projects that require interviews, the use of quotas ensures that the
appropriate sub-groups are identified and included in the survey. The quota

--- Content provided by⁠ FirstRanker.com ---

sampling method may eliminate or reduce selection bias on the part of the field
workers. An inherent limitation of quota sampling is that the success of the
study will be dependent on subjective decisions made by the researchers. Also,
it is incapable of measuring the true representativeness of the sample or
accuracy of the estimate obtained. Hence, attempts to generalise data results

--- Content provided by‌ FirstRanker.com ---

beyond those respondents who were sampled and interviewed become very
questionable and may misrepresent the defined target population.

Snowball Sampling

--- Content provided by​ FirstRanker.com ---


Snowball Sampling involves the practice of identifying and qualifying a

set of initial prospective respondents who can, in turn, help the researcher
identify additional people to be included in the study. This method of sampling

--- Content provided by‌ FirstRanker.com ---

is also called referral sampling, because one respondent refers other potential
respondents. Snowball sampling is typically used in research situations where :


i. the defined target population is very small and unique, and

--- Content provided by‌ FirstRanker.com ---




ii. compiling a complete list of sampling units is a nearly impossible

--- Content provided by‍ FirstRanker.com ---

task.
The snowball method would yield better results at a much lower cost. Here the
researcher would identify and interview one qualified respondent, then solicit
his or her help in identifying other people with similar characteristics. The main
underlying logic of this method is that rare groups of people tend to form their

--- Content provided by FirstRanker.com ---

own unique social circles.

Advantages and Disadvantages


--- Content provided by‍ FirstRanker.com ---

Snowball sampling is a reasonable method of identifying and selecting

prospective respondents who are members of small, hard-to-reach, uniquely
defined target population. It is most useful in qualitative research practices, like
focus group interviews. Reduced sample sizes and costs are primary advantages

--- Content provided by‌ FirstRanker.com ---

to this sampling method. Snowball sampling definitely allows bias to enter the
overall research study.



--- Content provided by FirstRanker.com ---

Activity. 2.6.



Co

--- Content provided by⁠ FirstRanker.com ---


m

pa r e

--- Content provided by‍ FirstRanker.com ---

a

nd contrast various non-probability sampling methods. Prepare a chart

showing their relative merits and demerits.

--- Content provided by‌ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

2.6. Random-Digit Dialing (RDD)


If truly accurate or representative, current sampling frames are not

--- Content provided by‍ FirstRanker.com ---

available, a researcher would have to employ an alternate method such as
random-digit dialing, if conducting telephone interviews. The only solution to
the problem of unlisted telephone numbers is to generate phone numbers by
some random process. This practice, referred to as Random-Digit Dialing
involves generation of random numbers at random. But practical considerations

--- Content provided by‍ FirstRanker.com ---

complicate the problem greatly. The foremost is the relatively small proportion
of the working numbers among all possible 10-digit telephone numbers. Only
about 1 in 170 of all possible telephone numbers is actually in use. The
proportion of the working residential numbers in RDD samples can be increased
dramatically by selecting from only the 103 working area codes ( first three

--- Content provided by​ FirstRanker.com ---

digits). The approach yields approximately 1 working residential number for
every 17 randomly generated. From a cost stand point, this rate is still low,
entailing too many unproductive dialings while including a proportionate
number of unlisted phone homes in the sample. There are three alternative
approaches built around the use of a telephone book.

--- Content provided by⁠ FirstRanker.com ---


Four-Digit approach


Taking the four-digit approach, the researcher must, in addition to

--- Content provided by​ FirstRanker.com ---


restricting the sample to the 103 working area codes, select numbers only from
working central offices or exchanges. The lat four digits of the number are
generated via some process that approaches randomness. Problem with this
approach is that all exchanges have an equal probability of being selected, while

--- Content provided by⁠ FirstRanker.com ---

some have a high proportion of all possible numbers in service and others have
only a small proportion in service.

Three-Digit approach

--- Content provided by FirstRanker.com ---


The next logical progression in RDD is the three-digit dialing approach.

This method increases the proportion of working numbers to better than one in
three. Consulting the section of a criss-cross directory where phone numbers are

--- Content provided by​ FirstRanker.com ---

listed numerically will show that within a particular exchange, certain sequences
of 1000 numbers are totally unused while other groups of 1000 are in use.
Generate the last three digits of each exchange by means of some random
process. This method is more efficient in eliminating non working numbers, but
increases bias due to missing new exchanges that have been activated.

--- Content provided by‍ FirstRanker.com ---





The four digit method is safer from the standpoint of avoiding bias, but

--- Content provided by⁠ FirstRanker.com ---


more expensive due to the greater number of calls that must be made. It is
suggested that three-digit method is most appropriate when the directories for
the area of interest are relatively current or when there has been little growth in
the area since the publication of the re cent directory. In other cases, the four-

--- Content provided by⁠ FirstRanker.com ---

digit method should be used.

Using telephone books


--- Content provided by FirstRanker.com ---

RDD samples can also be generated from the telephone book. This is

accomplished by selecting numbers at random from the book and adding a
random number as the sixth or seventh digit. Somewhere between one in two
and one in three of the numbers generated will be working residential numbers.

--- Content provided by‌ FirstRanker.com ---

This is a viable approach because, all exchanges are proportionately represented
in the book. The phone book is recommended as an RDD sample source only in
those cases where the appropriate computer hardware and software are not
available. There are two major reasons for making this recommendation. First,
the construction of sample by this approach is time-consuming and expensive.

--- Content provided by‌ FirstRanker.com ---

Second, if the interviewers are given directions and left to generate numbers
themselves, the researcher loses all control over the validity of the sample.
Computer programmes can incorporate three- or four- digit approaches and
generate RDD samples at a very low cost. The print-out can be set up to capture
additional data and to help the researcher control field costs and proper

--- Content provided by​ FirstRanker.com ---

execution of the sampling plan.



Activity 2.7.

--- Content provided by​ FirstRanker.com ---




Identify a situation where you would be in favour of using a non-probability

--- Content provided by‌ FirstRanker.com ---



sampling method over probability sampling method.


--- Content provided by‌ FirstRanker.com ---




2.7. Sample size

--- Content provided by‌ FirstRanker.com ---


Determining the appropriate sample size is not an easy task. The

researcher must consider how precise the estimates must be and how much time
and money are available to collect the required data, since the data collection is

--- Content provided by‌ FirstRanker.com ---

one of the most expensive components of a study. Three factors play an
important role in determining appropriate sample sizes. They are :
i. The variability of the population characteristic under consideration : The

greater the variability of the characteristic, the larger the size of the sample

--- Content provided by‌ FirstRanker.com ---

necessary.


ii. The level of confidence desired in the estimate : The higher the level of

--- Content provided by⁠ FirstRanker.com ---

confidence desired, the larger the sample size needed.

iii. The degree of precision desired in estimating the population characteristic :

The more precise the required sample results, the larger the necessary sample

--- Content provided by‍ FirstRanker.com ---

size.


2.7.1. Estimating the sample size by traditional methods

--- Content provided by‍ FirstRanker.com ---


There are four traditional approaches to determine the sample size. They

are :
i. Judgementally / arbitrarily : The researcher can simply select a sample size

--- Content provided by​ FirstRanker.com ---


arbitrarily or on the basis of some judgementally based criterion.. There may
be instances where the sample size represents all that where available at a
particular point of time.

--- Content provided by FirstRanker.com ---

ii. Analysis considerations : Analysis considerations may decide the sample size.

Sample size may be determined from the minimum cell size needed.

iii. The budget : In certain cases, the budget may determine the sample size.

--- Content provided by FirstRanker.com ---

iv. Applying standard error : Sample size determination is based on specifying

the desired precision in advance and then applying the appropriate standard
error formula.

--- Content provided by​ FirstRanker.com ---

Two major classes of procedures are available for estimating the sample size

1. Confidence ? interval approach : This is based on the idea of

constructing confidence intervals around sample means or proportions.

--- Content provided by FirstRanker.com ---


2. Hypothesis-testing approach : This makes use of both type I error

(rejecting a true null hypothesis) and Type II error (accepting a false null
hypothesis).

--- Content provided by⁠ FirstRanker.com ---



Confidence ? interval approach


--- Content provided by⁠ FirstRanker.com ---

In this method, a confidence interval is constructed around sample based

mean or proportion. The standard error formulae are used for this purpose. This
can be explained with an example. Consider a researcher my have taken a
sample of 100 consumers and noted that their average per-capita consumption of

--- Content provided by‍ FirstRanker.com ---

orange juice was 2.6 litres per week. Pat studies indicate that the population
standard deviation T can be assumed to be 0.3 litre. With this information, we
can find a range around the sample mean level of 2.6 litres for which some pre-
specified probability statement can be made about the process underlying the
construction of such confidence intervals. Suppose that we want to set up a 95%

--- Content provided by​ FirstRanker.com ---

confidence interval around the sample mean of 2.6 litres. The standard error of
the mean can be computed as :
0.3


--- Content provided by​ FirstRanker.com ---



x= ----- = ---------- = 0.03

n 100

--- Content provided by‌ FirstRanker.com ---




From the table, we can find that the central 95% of the normal distribution lies
within C 1.96 Z variates.

--- Content provided by FirstRanker.com ---

95% confidence interval ranges from 2.54 to 2.66 litres. Thus the pre- assigned
chance of finding the true population mean to be within 2.54 and 2.66 litres is
95%.

The case of sample mean

--- Content provided by​ FirstRanker.com ---



Following are the steps involved :

1. Specify the amount of error (E) that can be allowed. This is the maximum

--- Content provided by‌ FirstRanker.com ---


allowable difference between the sample mean and the population mean. 8 C
E defines the interval within which 0 will lie with some pre-specified level
of confidence.

--- Content provided by FirstRanker.com ---

2. Specify the desired level of confidence. It can be 95%.
3. Determine the number of standard errors (Z) associated with the confidence

level.

--- Content provided by‍ FirstRanker.com ---

4. Estimate the standard deviation of the population. The standard deviation can

be estimated by judgment, by reference to other studies or by the use of a
pilot sample.

--- Content provided by⁠ FirstRanker.com ---

5. Calculate the sample size using the formula for the standard error of the
mean.



--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---



E


--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

x = -------




--- Content provided by‍ FirstRanker.com ---


Z

6. Neglacting the finite multiplier, we solve for n in the formula

--- Content provided by‍ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---





E

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by FirstRanker.com ---





x = ------- = ------

--- Content provided by‍ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

Z

n


--- Content provided by​ FirstRanker.com ---

7. In general we can find n from the formula




--- Content provided by FirstRanker.com ---






--- Content provided by FirstRanker.com ---

2 Z2




--- Content provided by FirstRanker.com ---




n = --------------

--- Content provided by‌ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---




E2

--- Content provided by FirstRanker.com ---



The case of sample proportion


--- Content provided by⁠ FirstRanker.com ---


The procedure for determining sample size for interval estimates of proportion
are :
1. Specify the amount of error that can be allowed. Suppose that the desired

--- Content provided by⁠ FirstRanker.com ---

reliability is such that an allowable interval of p ? A = ? 0.05 is set, the
allowable error E is 0.05.

2. Specify the desired level of confidence. Suppose that the level of confidence

--- Content provided by‍ FirstRanker.com ---

is 95%.

3. Determine the number of standard errors (Z) associated with the confidence

level.

--- Content provided by‌ FirstRanker.com ---


4. Estimate the population proportion. (A). The population proportion can be

estimated by judgment, by reference to other studies or by the use of a pilot
sample.

--- Content provided by‌ FirstRanker.com ---


5. Calculate the sample size using the formula for the standard error of the

proportion.

--- Content provided by‌ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---





E

--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---





p= -----

--- Content provided by​ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---


Z

6. Neglacting the finite multiplier, we solve for n in the formula

--- Content provided by‌ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---


E ______________



--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---


p = ----- = A ( 1- A ) / n



--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---




Z

--- Content provided by​ FirstRanker.com ---


7. We can find n from the formula



--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---




A ( 1- A ) Z2

--- Content provided by​ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---




n = -------------------------------

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---



E2


--- Content provided by​ FirstRanker.com ---


Hypothesis testing approach

Sample size can also be determined by the hypothesis testing approach. For this,
an assumed probability of making Type I error ( called alpha risk) and the

--- Content provided by FirstRanker.com ---

probability of making Type II error ( called beta risk) are needed. These risks
are based on the hypotheses :


H0 : the null hypothesis

--- Content provided by FirstRanker.com ---



H1 : the alternate hypothesis

In hypothesis testing, the sample results sometimes lead us to reject H0 when its

--- Content provided by​ FirstRanker.com ---


is true. This is a type I error. On other occasions, the sample findings may lead
us to accept H0 when it is false. This is a Type II error.


--- Content provided by‍ FirstRanker.com ---


The case involving means



--- Content provided by⁠ FirstRanker.com ---


The steps are :



--- Content provided by​ FirstRanker.com ---

1. Specify the values for the null (H0) and the alternate (H1) hypotheses to

be tested in terms of population means, 0 and 1 respectively.

2. Specify the allowable probabilities ( and respectively) of Type I and

--- Content provided by‍ FirstRanker.com ---


Type II errors. The Type I error is the error of rejecting a true null
hypothesis. The Type II error is made if the alternate hypothesis is
rejected when it is true. and are the allowable probabilities of making
those two types of errors respectively.

--- Content provided by‍ FirstRanker.com ---


3. Determine the number of standard errors associated with each of the

error probabilities and .

--- Content provided by FirstRanker.com ---

4. Estimate the population standard deviation .
5. Calculate the sample size that will meet the and error requirements.

Since two sampling distributions are involved, a simultaneous solution of
two equations is required to determine the sample size and critical value

--- Content provided by FirstRanker.com ---

that will satisfy both equations. These equations are :




--- Content provided by‌ FirstRanker.com ---



Critical value = 0 + Z [ ----- ]


--- Content provided by​ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---



n


--- Content provided by​ FirstRanker.com ---





Critical value = 1 - Z [ ----- ]

--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---





n

--- Content provided by FirstRanker.com ---


6. Setting the right hand side of these two equations equal and solving for

n gives

--- Content provided by‍ FirstRanker.com ---



(Z + Z)2 2

n = -----------------

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

(1 - 0)2




--- Content provided by⁠ FirstRanker.com ---

The case involving proportions



The steps are :

--- Content provided by​ FirstRanker.com ---



1. Specify the values for the null (H0) and the alternate (H1) hypotheses to

be tested in terms of population proportions, 0 and 1 respectively.

--- Content provided by​ FirstRanker.com ---


2. Specify the allowable probabilities ( and respectively) of Type I and

Type II errors.

--- Content provided by FirstRanker.com ---

3. Determine the number of standard errors associated with each of the

error probabilities Z and Z.

4. Calculate the desired sample size n from the formula :

--- Content provided by FirstRanker.com ---




2

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---



Z [0 (1- 0)] + Z [1 (1- 1)]


--- Content provided by​ FirstRanker.com ---






--- Content provided by FirstRanker.com ---



n = -------------------------------------------------


--- Content provided by‍ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---


1 - 0



--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---





2.7.2. Bayesian approach to sample size determination

--- Content provided by‍ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

Bayesian procedures are based on the central principle that one should

select the sample size that results in the largest positive difference between the
expected payoff of sample information and the estimated cost of sampling. The
difference between the expected payoff of the sample information and the

--- Content provided by⁠ FirstRanker.com ---

estimated cost of sampling is frequently referred to as the expected net gain
from sampling. An equivalent way of stating the principle is that one should
select the sample size that leads to the largest expected net gain from sampling.


--- Content provided by​ FirstRanker.com ---



In a decisional situation in which one of the primary objectives is to

maximize payoff, this rule is appropriate. The general approach to applying it

--- Content provided by FirstRanker.com ---

requires the decision maker to :


- Determine the expected value of the sample information for a given

--- Content provided by‍ FirstRanker.com ---

sample size.


- Estimate the sampling cost for that specific option.
- Find the expected net gain from sampling under that option.

--- Content provided by⁠ FirstRanker.com ---

- Search through other sample sizes to find the one that leads to the

highest expected net gain from sampling.

While logically sound concept, the Bayesian approach is difficult to implement.

--- Content provided by​ FirstRanker.com ---

The primary problem comes in operationalising the first of the steps stated
above. In order to determine the expected value of the sample information for a
given sample size, one must relate the sample size being considered to the
conditional probabilities of making errors, including the effects of non-sampling
errors. In real life situations, this may become very difficult to do.

--- Content provided by⁠ FirstRanker.com ---


2.8. Sampling error


Several potential sources of error can affect the quality of a research

--- Content provided by‍ FirstRanker.com ---


process. The errors can influence the various stages of the research process and
result in inaccurate or useless research findings. Researchers have numerous
opportunities to make mistakes or errors in judgment, that result in creating
some type of bias in any research study. All types of errors can be logically

--- Content provided by‍ FirstRanker.com ---

classified as either sampling or non-sampling errors. Random sampling errors
can be detected by observing the difference between the sample results and the
results of a census conducted using identical procedures. Two difficulties are
associated with detection of the sampling error :

--- Content provided by‌ FirstRanker.com ---


i. the fact that very seldom is a census conducted in survey research

and

--- Content provided by​ FirstRanker.com ---

ii. sampling error can be determined only after the sample is drawn
and data collection has been completed.

The Total Error in a research study is the difference between the true mean value
(within the population) of the variable being studied and the observed mean

--- Content provided by‍ FirstRanker.com ---

value obtained through the research study.




--- Content provided by⁠ FirstRanker.com ---


To tal Error



--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---



Sampling Error

Non-sampling

--- Content provided by‌ FirstRanker.com ---




Error

--- Content provided by​ FirstRanker.com ---





Design Errors

--- Content provided by FirstRanker.com ---


Administering

Response Errors

--- Content provided by​ FirstRanker.com ---

Non response

Errors

Error

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---


Sampling error is any type of bias that is attributable to mistakes made in

either the selection process of prospective sampling units or determining the
sample size. Sampling error is the difference between a measure obtained from a

--- Content provided by FirstRanker.com ---

sample representing the population and the true measure that can be obtained
only from the entire population. This error occurs because no sample is a perfect
representation of a given population, unless the sample size equals the
population. Random sampling error tends to occur because of chance variations
in the scientific selection of the needed sample units. Even if the sampling units

--- Content provided by⁠ FirstRanker.com ---

were properly selected according to the guidelines of sampling theory, those
units still might not be a perfect representation of the defined target population.
When there is a discrepancy between the statistic calculated or estimated from
the sample and the actual value from the population, a sampling error has
occurred. Based on the principles of the central limit theorem, the size of the

--- Content provided by⁠ FirstRanker.com ---

sampling error and its impact can be reduced by increasing the size of the
sample.



--- Content provided by‍ FirstRanker.com ---




Ways to minimize sampling error

--- Content provided by​ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---


1. Increase the sample size.



--- Content provided by​ FirstRanker.com ---

2. Use a statistically efficient sampling plan. That is making the sample as representative of

the population as possible.


--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

Non-sampling errors are those types of biases that occur in a research

study regardless of whether a sample or census is used. There may be several
reasons for these errors. Non-sampling errors can be broadly classified into four
groups :

--- Content provided by⁠ FirstRanker.com ---


ii.

Design errors

--- Content provided by⁠ FirstRanker.com ---

iii.

Administering errors

iv.

--- Content provided by⁠ FirstRanker.com ---


Response errors

v.

--- Content provided by​ FirstRanker.com ---

Non response errors.


i. Design errors : Design errors also called researcher- induced errors are
mainly

--- Content provided by FirstRanker.com ---


due to flaws in the research design. These errors can take various

forms.

--- Content provided by FirstRanker.com ---


Selection error : This occurs when a sample obtained through a non



--- Content provided by​ FirstRanker.com ---

probability sampling method is not representative of the population.




--- Content provided by‌ FirstRanker.com ---

Population specification error : This occurs when an inappropriate

population

is chosen from which to obtain data for the research study.

--- Content provided by⁠ FirstRanker.com ---




Sampling frame error : It occurs when the sample is drawn from an

--- Content provided by​ FirstRanker.com ---



inaccurate sampling frame.


--- Content provided by FirstRanker.com ---


Surrogate information error : It is the difference between the information
required for a research study and the information being sought by the
researcher.

--- Content provided by⁠ FirstRanker.com ---



Measurement error : It is the difference between the information sought
by the researcher for a study and the information generated by a
particular measurement method employed by the researcher.

--- Content provided by⁠ FirstRanker.com ---




Experimental error : Any error caused by the improper design of the
experiment induce an experimental error into the study.

--- Content provided by​ FirstRanker.com ---




Data analysis error : This can occur when the data from the questionnaires
are coded, edited, analysed or interpreted.

--- Content provided by​ FirstRanker.com ---


ii. Administering errors : All errors that occur during the administration of a

survey instrument to the respondents are classified as administering
errors. They are caused by the person administering the questionnaire.

--- Content provided by⁠ FirstRanker.com ---

They may be caused by three major factors :



Questioning error : This error arises while addressing questions to the

--- Content provided by​ FirstRanker.com ---

respondents.



Recording error : This arises from improperly recording the respondent`s

--- Content provided by⁠ FirstRanker.com ---

answers.



Inference error : This error occurs when an interviewer interferes with or

--- Content provided by FirstRanker.com ---

fails to follow the exact procedure while collecting data.

iii. Response errors : Also called data errors occur when the respondent

intentionally or unintentionally provides inaccurate answers to the survey

--- Content provided by​ FirstRanker.com ---

questions.

iv. Non-response errors : These occur if some members of a sample were not

contacted or some of the members contacted provide no response to the

--- Content provided by⁠ FirstRanker.com ---

survey.




--- Content provided by‌ FirstRanker.com ---

2.9. Non-response Problems

The object of sampling is to obtain a body of data that are representative

of the population. Unfortunately, some sample members become non-

--- Content provided by​ FirstRanker.com ---

respondents because they :

i. refuse to respond,


--- Content provided by‍ FirstRanker.com ---


ii. lack the ability to respond,
iii. are not at home, or


--- Content provided by FirstRanker.com ---

iv. are inaccessible.

Non-response can be a serious problem. If a sample size of 1,000 is needed and
only a 50 percent response rate is expected, then 2,000 people will need to be
identified as possible sample members. The seriousness of non-response bias

--- Content provided by FirstRanker.com ---

depends on the extent of the non-response. If the percentage involved is small,
the bias is small. The non-response problem depends on how the non-
respondents differ from the respondents, particularly on the key questions of
interest. To deal with non-response problem tendency will be to replace each
non-respondent with a "matched" member of the sample. The difficulty is that

--- Content provided by‌ FirstRanker.com ---

the replacement cannot be matched easily on the characteristic that prompted the
non-response, such as being employed or being a frequent traveller. Three
approaches are :

i. to improve the research design to reduce the number of non-responses,

--- Content provided by​ FirstRanker.com ---

ii. to repeat the contact one or more times (call-backs) to try to reduce

non-responses, and

iii. to attempt to estimate the non-response bias.

--- Content provided by​ FirstRanker.com ---


Improving the research Design

The challenge in personal and telephone interviewing is to gain initial

--- Content provided by‌ FirstRanker.com ---

interest and to generate rapport through interviewer skill and the design and
placement of questions. In mail surveys, the task is to motivate the respondent to
respond, through incentives and other devices. The number of not-at-homes can
be reduced by scheduling calls with some knowledge of the respondents` likely
activity patterns.

--- Content provided by​ FirstRanker.com ---


Call-Backs

Call-backs refer to new attempts to obtain responses. The use of call-

--- Content provided by⁠ FirstRanker.com ---

backs is predicated on the assumption that they will generate a useful number of
additional responses and that the additional responses will reduce meaningfully
a non-response bias. If the non-response is due to refusals or the inability to
respond, call-backs may not reduce significantly the number of non-respondents.
They are most effective for the not-at-home non-respondent. The efficiency of

--- Content provided by‌ FirstRanker.com ---

the call-backs will be improved by scheduling them at different times of the day
and week. In a mail survey, the call-back is particularly important, because the
non-response level can be high. It is common practice to remind non-
respondents at regular intervals.

--- Content provided by‍ FirstRanker.com ---

Estimating the Effects of Non-response
One approach is to make an extra effort to interview a sub-sample of the non-
respondents. In the case of a mail survey, the sub-sample might be interviewed
by telephone. In a telephone or personal survey, an attractive incentive, such as a

--- Content provided by​ FirstRanker.com ---


worthwhile gift, might be employed to entice a sample of the non-respondents to
co-operate.


--- Content provided by⁠ FirstRanker.com ---




Summary

--- Content provided by‌ FirstRanker.com ---





Sampling is an important concept that we practice in our every day life.

--- Content provided by‌ FirstRanker.com ---




Sampling involves selecting a relatively small number of elements from a larger

--- Content provided by FirstRanker.com ---



defined group of elements and expecting that the information gathered from the small


--- Content provided by‌ FirstRanker.com ---


group will allow judgments to be made about the larger group. If all the respondents



--- Content provided by‍ FirstRanker.com ---

in a population are asked to provide information, such survey is called a census.



Information obtained from a subset of the population is known as the statistic (from

--- Content provided by​ FirstRanker.com ---

sample).



Selection of the most appropriate sampling design should incorporate the

--- Content provided by​ FirstRanker.com ---




seven factors. They are : Research objectives, Degree of accuracy, Availability of

--- Content provided by⁠ FirstRanker.com ---



resources, Time frame, Advanced knowledge of the target population, Scope of the


--- Content provided by​ FirstRanker.com ---


research and Perceived statistical analysis needs. A sampling plan is the blueprint or



--- Content provided by⁠ FirstRanker.com ---

frame work needed to ensure that the raw data collected are representative of the
defined target population.



--- Content provided by⁠ FirstRanker.com ---

There are two basic sampling designs : Probability and non-probability



sampling methods. In probability sampling, each unit in the defined target population

--- Content provided by​ FirstRanker.com ---




has a known, non-zero probability of being selected for the sample, The actual

--- Content provided by FirstRanker.com ---



probability of selection for each sampling unit may or may not be equal depending on


--- Content provided by⁠ FirstRanker.com ---


the type of probability sampling design used. It allows the researcher to judge the
reliability and validity of raw data collected by calculating the probability to which


--- Content provided by​ FirstRanker.com ---


the findings based on the sample would differ from the defined target population.



--- Content provided by‌ FirstRanker.com ---

The results obtained by the probability method can be generalized to the target



population within a specified margin of error through the use of statistical methods.

--- Content provided by⁠ FirstRanker.com ---




In non-probability sampling, the probability of selection of each sample unit is not

--- Content provided by‍ FirstRanker.com ---



known. Therefore, potential sampling error cannot be accurately known either. The
selection of sampling units is based on some type of intuitive judgments, desire or

--- Content provided by‌ FirstRanker.com ---



knowledge of the researcher. The degree to which the sample may or may not be


--- Content provided by⁠ FirstRanker.com ---


representative of the defined target population depends on the sampling approach and



--- Content provided by‌ FirstRanker.com ---

how well the researcher executes and controls the selection activities. There is always



a temptation to generalize non-probability sample data results to the defined target

--- Content provided by‌ FirstRanker.com ---




population.

--- Content provided by‌ FirstRanker.com ---

Various probability sampling methods are : a. Simple random sampling, b.



Systematic Random Sampling, c. Stratified Random Sampling, d. Cluster Sampling ,

--- Content provided by‌ FirstRanker.com ---




e. Area sampling. Non-probability sampling methods can be classified as : a.

--- Content provided by FirstRanker.com ---



Convenience Sampling, b. Judgment Sampling, c. Quota Sampling, d. Snowball


--- Content provided by‌ FirstRanker.com ---


Sampling.



--- Content provided by⁠ FirstRanker.com ---

Random-Digit Dialing involves generation of random numbers at random. If

truly accurate or representative, current sampling frames are not available, a


--- Content provided by‍ FirstRanker.com ---


researcher would have to employ an alternate method such as random-digit dialing, if



--- Content provided by​ FirstRanker.com ---

conducting telephone interviews.



The traditional approaches in determining the sample size are :

--- Content provided by⁠ FirstRanker.com ---




i. Judgementally / arbitrarily, ii. Analysis considerations, iii. The budget, iv.

--- Content provided by‍ FirstRanker.com ---



Applying standard error. Bayesian procedures are based on the central principle that
one should select the sample size that results in the largest positive difference

--- Content provided by FirstRanker.com ---



between the expected payoff of sample information and the estimated cost of


--- Content provided by FirstRanker.com ---


sampling.



--- Content provided by​ FirstRanker.com ---

Sampling error is the difference between a measure obtained from a sample

representing the population and the true measure that can be obtained only from the


--- Content provided by​ FirstRanker.com ---


e n t i r e

po pulation. The Total Error in a research study is the difference between the

--- Content provided by‍ FirstRanker.com ---

true mean value (within the population) of the variable being studied and the
observed mean value obtained through the research study. Total error can be
classified into sampling error and non-sampling error.


--- Content provided by‍ FirstRanker.com ---


Some sample members become non-respondents because they : i. refuse to

respond, ii. lack the ability to respond, iii. are not at home, or iv. are inaccessible.

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---



Self Assessment Questions

1. Define sampling.

--- Content provided by​ FirstRanker.com ---

2. Give the differences between census and sampling.
3. Define the following :


Population

--- Content provided by​ FirstRanker.com ---




Element

--- Content provided by‍ FirstRanker.com ---



Sampling units


--- Content provided by‍ FirstRanker.com ---


Sampling frame



--- Content provided by FirstRanker.com ---

Sampling gap



Sampling distribution

--- Content provided by FirstRanker.com ---


4. What is Central Limit Theorem ?
5. What are the factors influencing the selection of a sampling design ?
6. Define sampling plan. What are the steps in developing a sampling plan ?
7. Differentiate between probability and non-probability sampling methods.

--- Content provided by‍ FirstRanker.com ---

8. What are the types of probability sampling methods ?
9. Define the following :


Simple random sampling

--- Content provided by⁠ FirstRanker.com ---




Systematic Random Sampling

--- Content provided by‌ FirstRanker.com ---



Stratified Random Sampling


--- Content provided by‌ FirstRanker.com ---


Cluster Sampling



--- Content provided by⁠ FirstRanker.com ---

Area sampling

10. What are the types of non-probability sampling methods ?
11. Define the following :

--- Content provided by⁠ FirstRanker.com ---


Convenience Sampling



--- Content provided by FirstRanker.com ---

Judgment Sampling



Quota Sampling

--- Content provided by​ FirstRanker.com ---




Snowball Sampling

--- Content provided by FirstRanker.com ---

12. What is Random-Digit Dialing (RDD) ?
13. What are the factors in determining appropriate sample sizes ?
14. What are the traditional approaches in determining the sample size ?
15. What is Bayesian approach to sample size determination ?
16. What is sampling error ? What are the types of total error ?

--- Content provided by​ FirstRanker.com ---

17. What are the types of non-sampling errors ?
18. What are the reasons for non-response of respondents ?

Answer Key

--- Content provided by⁠ FirstRanker.com ---

1. Sampling involves selecting a relatively small number of elements from a larger
defined group of elements and expecting that the information gathered from the small
group will allow judgments to be made about the larger group.
2. If all the respondents in a population are asked to provide information, such survey is
called a census. A subset of the population is known as the sample.

--- Content provided by‍ FirstRanker.com ---



3. a. Population : A population is an identifiable total group or aggregation of elements
that are of interest to the researcher and pertinent to the specified problem.
b. Element : An element is a person or object from which data and information are

--- Content provided by FirstRanker.com ---

sought.
c. Sampling units : Sampling units are the target population elements available for
selection during the sampling process.
d. Sampling frame : Sampling frame is the list of all eligible sampling units.
e. Sampling gap : A sampling gap is the representation difference between the

--- Content provided by FirstRanker.com ---

population elements and sampling units in the sampling frame.
f. Sampling distribution : Sampling distribution is the frequency distribution of a
specific sample statistic ( sample mean or sample proportion ) from repeated random
samples of the same size.
4. The theorem states that for almost all defined target populations, the sampling

--- Content provided by​ FirstRanker.com ---

distribution of the mean or the percentage value derived from a simple random sample
will be approximately normally distributed, provided that the sample size is sufficiently
large.
5. Research objectives, Degree of accuracy, Availability of resources, Time frame,
Advanced knowledge of the target population, Scope of the research and Perceived

--- Content provided by​ FirstRanker.com ---

statistical analysis needs.
6. A sampling plan is the blueprint or frame work needed to ensure that the raw data
collected are representative of the defined target population. A good sampling plan will
include, the following steps: (1) define the target population, (2) select the data
collection method, (3) identify the sampling frames needed, (4) select the appropriate

--- Content provided by⁠ FirstRanker.com ---

sampling method, (5) determine necessary sample sizes and overall contact rates, (6)
create an operating plan for selecting sampling units, and (7) execute the operational
plan.
7. ________________________________________________________________

--- Content provided by‌ FirstRanker.com ---





Factor

--- Content provided by​ FirstRanker.com ---




Probability sampling

--- Content provided by FirstRanker.com ---



Non-probability


--- Content provided by FirstRanker.com ---


sampling



--- Content provided by‍ FirstRanker.com ---

_____________________________________________________________________________




--- Content provided by⁠ FirstRanker.com ---




a. List of the population elements Complete list necessary

--- Content provided by⁠ FirstRanker.com ---

Not necessary




--- Content provided by‌ FirstRanker.com ---

b. Information about the-

Each unit identified


--- Content provided by⁠ FirstRanker.com ---


need detail on habits,



--- Content provided by​ FirstRanker.com ---

sampling units




--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---

activities, traits etc.




--- Content provided by⁠ FirstRanker.com ---




c. Sampling skill

--- Content provided by‍ FirstRanker.com ---



skill required


--- Content provided by‍ FirstRanker.com ---




little skill required

--- Content provided by FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---


d. Time requirement



--- Content provided by​ FirstRanker.com ---

More time-consuming



Less time consuming

--- Content provided by​ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

e. Cost per unit sampled

Moderate to high


--- Content provided by⁠ FirstRanker.com ---


Low



--- Content provided by‍ FirstRanker.com ---





f. Estimate of population -

--- Content provided by‌ FirstRanker.com ---


Unbiased



--- Content provided by​ FirstRanker.com ---



Biased


--- Content provided by​ FirstRanker.com ---


parameters



--- Content provided by⁠ FirstRanker.com ---



g. Sample representativeness

Assured

--- Content provided by FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

Undeterminable




--- Content provided by​ FirstRanker.com ---




h.

--- Content provided by‌ FirstRanker.com ---

A c

c u

r a

--- Content provided by FirstRanker.com ---


c y a

nd

--- Content provided by‍ FirstRanker.com ---



Computed with


--- Content provided by‍ FirstRanker.com ---


Unknown

Reliability

--- Content provided by FirstRanker.com ---



confidence intervals


--- Content provided by​ FirstRanker.com ---

i. Measurement of sampling error Statistical measures



No true measure

--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---



available


--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

8.

a. Simple random sampling


--- Content provided by‍ FirstRanker.com ---


b. Systematic Random Sampling



--- Content provided by​ FirstRanker.com ---

c. Stratified Random Sampling



d. Cluster Sampling

--- Content provided by​ FirstRanker.com ---




e. Area sampling.

--- Content provided by FirstRanker.com ---

9.
a. Simple random sampling : Simple Random Sampling is a probability sampling
procedure which ensures that every sampling unit making up the defined target
population has a known, equal, non-zero chance of being selected.
b. Systematic Random Sampling : Systematic random sampling (SYMRS) is similar to

--- Content provided by‌ FirstRanker.com ---

simple random sampling but requires that the defined target population be ordered in
some way, usually in the form of a customer list, taxpayer roll, or membership roster.
c. Stratified Random Sampling : Stratified random sampling (STRS) requires the
separation of the defined target population into different groups, called strata, and the
selecting of samples from each stratum.

--- Content provided by⁠ FirstRanker.com ---

d. Cluster Sampling : The sampling units are divided into mutually exclusive and
collectively exhaustive sub-populations, called clusters. Each cluster is assumed to be
representative of the heterogeneity of the target population.
e. Area sampling :The clusters are formed by geographic designations. Examples
include cities, sub divisions and blocks.

--- Content provided by⁠ FirstRanker.com ---

10.

a. Convenience Sampling


--- Content provided by FirstRanker.com ---


b. Judgment Sampling



--- Content provided by‌ FirstRanker.com ---

c. Quota Sampling



d. Snowball Sampling

--- Content provided by‌ FirstRanker.com ---


11.
a. Convenience Sampling : Convenience sampling (or accidental sampling) is a method
in which samples are drawn at the convenience of the researcher or interviewer.
b. Judgment Sampling : In judgment sampling, (also referred to as purposive sampling),

--- Content provided by​ FirstRanker.com ---

participants are selected according to an experienced individual's belief that they will
meet the requirements of the study.
c. Quota Sampling : The quota sampling method involves the selection of prospective
participants according to pre-specified quota regarding either demographic
characteristics, specific attitudes, or specific behaviours.

--- Content provided by‍ FirstRanker.com ---

d. Snowball Sampling : Snowball Sampling involves the practice of identifying and
qualifying a set of initial prospective respondents who can, in turn, help the researcher
identify additional people to be included in the study.


--- Content provided by‍ FirstRanker.com ---

12. Random-Digit Dialing involves generation of random numbers at random. If truly
accurate or representative, current sampling frames are not available, a researcher
would have to employ an alternate method such as random-digit dialing, if conducting
telephone interviews.
13.

--- Content provided by​ FirstRanker.com ---


i. The variability of the population characteristic under consideration.
ii. The level of confidence desired in the estimate.
iii. The degree of precision desired in estimating the population characteristic.

--- Content provided by‍ FirstRanker.com ---

14.

i. Judgementally / arbitrarily.
ii. Analysis considerations.
iii. The budget.

--- Content provided by⁠ FirstRanker.com ---

iv. Applying standard error.

15. Bayesian procedures are based on the central principle that one should select the
sample size that results in the largest positive difference between the expected payoff of
sample information and the estimated cost of sampling.

--- Content provided by FirstRanker.com ---

16. Sampling error is the difference between a measure obtained from a sample
representing the population and the true measure that can be obtained only from the
entire population. The Total Error in a research study is the difference between the true
mean value (within the population) of the variable being studied and the observed mean
value obtained through the research study. Total error can be classified into sampling

--- Content provided by‍ FirstRanker.com ---

error and non-sampling error.
17.Non-sampling errors can be broadly classified into four groups :


i. Design errors

--- Content provided by‍ FirstRanker.com ---




ii. Administering errors

--- Content provided by⁠ FirstRanker.com ---



iii. Response errors


--- Content provided by FirstRanker.com ---


iv. Non response errors

18. Some sample members become non-respondents because they :

--- Content provided by‍ FirstRanker.com ---


i. refuse to respond,



--- Content provided by‍ FirstRanker.com ---

ii. lack the ability to respond,



iii. are not at home, or

--- Content provided by‌ FirstRanker.com ---




iv. are inaccessible.

--- Content provided by⁠ FirstRanker.com ---

Glossary

Area sampling :The clusters are formed by geographic designations. Examples include cities,
sub divisions and blocks.
Cluster Sampling : The sampling units are divided into mutually exclusive and collectively

--- Content provided by FirstRanker.com ---

exhaustive sub-populations, called clusters. Each cluster is assumed to be representative of the
heterogeneity of the target population.
Convenience Sampling : Convenience sampling (or accidental sampling) is a method in which
samples are drawn at the convenience of the researcher or interviewer.
Element : An element is a person or object from which data and information are sought.

--- Content provided by‍ FirstRanker.com ---

Judgment Sampling : In judgment sampling, (also referred to as purposive sampling),
participants are selected according to an experienced individual's belief that they will meet the
requirements of the study.
Population : A population is an identifiable total group or aggregation of elements that are of
interest to the researcher and pertinent to the specified problem.

--- Content provided by​ FirstRanker.com ---



Quota Sampling : The quota sampling method involves the selection of prospective participants
according to pre-specified quota regarding either demographic characteristics, specific attitudes,
or specific behaviours.

--- Content provided by‌ FirstRanker.com ---

Random-Digit Dialing : Random-Digit Dialing involves generation of random numbers at
random. If truly accurate or representative, current sampling frames are not available, a
researcher would have to employ an alternate method such as random-digit dialing, if conducting
telephone interviews.
Sampling distribution : Sampling distribution is the frequency distribution of a specific sample

--- Content provided by‌ FirstRanker.com ---

statistic from repeated random samples of the same size.
Sampling frame : Sampling frame is the list of all eligible sampling units.
Sampling gap : A sampling gap is the representation difference between the population elements
and sampling units in the sampling frame.
Sampling units : Sampling units are the target population elements available for selection during

--- Content provided by‌ FirstRanker.com ---

the sampling process.
Simple random sampling : Simple Random Sampling is a probability sampling procedure which
ensures that every sampling unit making up the defined target population has a known, equal,
non-zero chance of being selected.
Snowball Sampling : Snowball Sampling involves the practice of identifying and qualifying a

--- Content provided by⁠ FirstRanker.com ---

set of initial prospective respondents who can, in turn, help the researcher identify additional
people to be included in the study.
Stratified Random Sampling : Stratified random sampling (STRS) requires the separation of the
defined target population into different groups, called strata, and the selecting of samples from
each stratum.

--- Content provided by FirstRanker.com ---

Systematic Random Sampling : Systematic random sampling (SYMRS) is similar to simple
random sampling but requires that the defined target population be ordered in some way, usually
in the form of a customer list, taxpayer roll, or membership roster.

________________________________________________________________

--- Content provided by‌ FirstRanker.com ---

_______

Reference

1. Paul. E. Green, Donald. S. Tull, Gerald Albaum, Research for Marketing Decisions,

--- Content provided by‌ FirstRanker.com ---


Prentice Hall of India Pvt. Ltd. New Delhi.

2. Joseph. F. Hair, Robert. P. Bush, David. J. Ortinan, Marketing Research, Tata

--- Content provided by⁠ FirstRanker.com ---

McGraw-Hill Publishing Company Ltd, New Delhi.

3. David. A. Aaker, V. Kumar, George.S.Day, Marketing Research, John Wiley & Sons

Inc, Singapore.

--- Content provided by​ FirstRanker.com ---


4. William. M.K. Trochim, Research Methods, Biztantra, New Delhi.



--- Content provided by​ FirstRanker.com ---



Unit III


--- Content provided by​ FirstRanker.com ---


THE MEASUREMENT



--- Content provided by FirstRanker.com ---

3.1 Introduction

3.2 Definition of measurement

3.3 Functions of measurement

--- Content provided by​ FirstRanker.com ---


3.4 Advantages and disadvantages of measurement

3.5 Uses of measurement in research

--- Content provided by‍ FirstRanker.com ---

3.6 Fundamentals of measurement

3.7 Types of measurement


--- Content provided by‍ FirstRanker.com ---


Learning objectives



--- Content provided by⁠ FirstRanker.com ---

To understand the concept of measurement

To learn about the measurement process and how to develop a good

measurement scale

--- Content provided by​ FirstRanker.com ---


To understand the four levels of scales and their typical usage

To explore the concepts of reliability and validity

--- Content provided by‍ FirstRanker.com ---

The business research revolves around measurement, which refers to obtaining

symbols to represent properties of objects, events or states. Measurement helps

in identifying attitudes of individuals .When we measure an object, essentially

--- Content provided by⁠ FirstRanker.com ---


all we are doing is counting the number of standard pieces it takes to be the

same size as the object.

--- Content provided by FirstRanker.com ---

Measurement is defined as:

The determination of size in relation to some observed standard, e.g. metre,

kilogram, second, ampere, degree Kelvin, candela, mole, or some unit derived

--- Content provided by‌ FirstRanker.com ---


from these seven basic units.



--- Content provided by FirstRanker.com ---

According to the famous British scientist, Lord Kelvin, "When you measure

what you are speaking about and express it in numbers, you know something

about it, but when you cannot (or do not) measure it, when you cannot (or do

--- Content provided by‍ FirstRanker.com ---


not) express it in numbers, then your knowledge is of a meager and

unsatisfactory kind."

--- Content provided by⁠ FirstRanker.com ---

Measurement is the process observing and recording the observations.

Measurement is the estimation or determination of extent, dimension or

capacity, usually in relation to some standard or unit of measurement. The

--- Content provided by FirstRanker.com ---


measurement is expressed as a number of units of the standard, such as distance

being indicated by a number of kilometers.

--- Content provided by⁠ FirstRanker.com ---

The process of measuring involves estimating the ratio of the magnitude of a

quantity to the magnitude of a unit of the same type length, time etc. A

measurement is the result of such a process, expressed as the product of a real

--- Content provided by FirstRanker.com ---


number and a unit, where the real number is the estimated ratio. Example is 100

meters, which is an expression of an object`s length relative to a unit of length,

--- Content provided by‌ FirstRanker.com ---

the meter etc.,

The fundamental ideas involved in measuring are nominal, ordinal, interval and

ratio. We consider four broad categories of measurements. Survey research

--- Content provided by​ FirstRanker.com ---


includes the design and implementation of interviews and questionnaires.

Scaling involves consideration of the major methods of developing and

--- Content provided by‌ FirstRanker.com ---

implementing a scale. Qualitative research provides an overview of the broad

range of non-numerical measurement approaches.


--- Content provided by‍ FirstRanker.com ---

Measurement is the assignment of numbers to objects in such a way that

physical relationships and operations among the objects correspond to arithmetic

relationships and operations among the numbers.

--- Content provided by​ FirstRanker.com ---


According to Dr D.D. Sharma, Measurement is concerned with correspondence

between empirical entities and a formal model of abstract elements or numbers

--- Content provided by FirstRanker.com ---

,the relationship among these elements and the operations which can be

performed on them. Such a rule of correspondence determines a scale.

According to S.S.Stevens, Measurement is the assignment of numerals to

--- Content provided by⁠ FirstRanker.com ---


objects or events according to rules.

According to Campbell,`` Measurement is the assignment of numbers to

--- Content provided by FirstRanker.com ---

represent properties.

CONCEPT OF MEASUREMENT


--- Content provided by FirstRanker.com ---


Measurement in quantitative research

Views regarding the role of measurement in quantitative research are somewhat

--- Content provided by‌ FirstRanker.com ---

divergent. Measurement is often regarded as being only a means by which

observations are expressed numerically in order to investigate causal relations or

associations. However, it has been argued that measurement often plays a more

--- Content provided by⁠ FirstRanker.com ---


important role in quantitative research. For example, Thomas Kuhn (1961)

argued that results that appear anomalous in the context of accepted theory

--- Content provided by‌ FirstRanker.com ---

potentially lead to the genesis of a search for a new, natural phenomenon. He

believed that such anomalies are most striking when encountered during the

process of obtaining measurements, as reflected in the following observations

--- Content provided by​ FirstRanker.com ---


regarding the function of measurement in science:


When measurement departs from theory, it is likely to yield mere numbers, and

--- Content provided by​ FirstRanker.com ---


their very neutrality makes them particularly sterile as a source of remedial

suggestions. However, numbers register the departure from theory with an

--- Content provided by⁠ FirstRanker.com ---

authority and finesse that no qualitative technique can duplicate, and that

departure is often enough to start a search (Kuhn, 1961, p. 180).


--- Content provided by​ FirstRanker.com ---


In classical physics, the theory and definitions, which underpin measurement,

are generally deterministic in nature. In contrast, probabilistic measurement

--- Content provided by​ FirstRanker.com ---

models known as the Rasch model and Item response theory models are

generally employed in the social sciences. Psychometrics is the field of study

concerned with the theory and technique for measuring social and psychological

--- Content provided by​ FirstRanker.com ---


attributes and phenomena. This field is central to much quantitative research that

is undertaken within the social sciences.

--- Content provided by‌ FirstRanker.com ---



Measurement may be defined as the assignment of numerals to

characteristics of objects , persons, states, or events, according to rules.

--- Content provided by FirstRanker.com ---


What is measured is not the objects, person, state, or event itself but

some characteristic of it. When objects are counted, for example, we do

--- Content provided by​ FirstRanker.com ---

not measure the object itself but only its characteristic of being present.

We never measure people, only their age, height, weight, or some other

characteristic.

--- Content provided by⁠ FirstRanker.com ---




LEVELS OF MEASUREMENT

--- Content provided by‌ FirstRanker.com ---



There are four levels of measurement: nominal, ordinal, interval and ratio.

We describe below the characteristics of each of these levels.

--- Content provided by FirstRanker.com ---





(1) Nominal measurement: Nominal measurement is the most

--- Content provided by FirstRanker.com ---


elementary method of measurement which classifies persons,

objects or events into a number of mutually exclusive

--- Content provided by⁠ FirstRanker.com ---

categories on the basis of the simple presence or absence,

applicability or inapplicability, possession or non-possession

of certain property. This is have` us. have nots`

--- Content provided by⁠ FirstRanker.com ---


measurement which assigns mutually exclusive labels to

identify objects. Thus, the population of a town may be

--- Content provided by‌ FirstRanker.com ---

classified according to gender into males` and females`

or according to religion into Hindus, Jains, Parsis, Muslims,

Sikhs and Christians and each category of persons given

--- Content provided by FirstRanker.com ---


certain labels either in the form of numerals (0,1,2,3) or in

the form of letters (A,B,C,D).

--- Content provided by‌ FirstRanker.com ---



These labels only tell us that the categories are

qualitatively different from each other. They have no

--- Content provided by⁠ FirstRanker.com ---


quantitative significance, i.e., they cannot be added,

subtracted, multiplied or divided. Once can, if one likes,

--- Content provided by⁠ FirstRanker.com ---

interchange the labels of various categories for they do not

signify any ranking or ordering of categories . The numeral

1 given to a certain category does not imply its superior

--- Content provided by‌ FirstRanker.com ---


position to other category which is given numeral 0.



--- Content provided by‍ FirstRanker.com ---

The only arithmetic operation possible in case of a nominal

measurement is counting. Thus, mode is the only legitimate

measure of central tendency. One can also calculate the

--- Content provided by‌ FirstRanker.com ---


percentage of objects failing within each category. But, it

will not make sense to calculate the arithmetic mean of

--- Content provided by‌ FirstRanker.com ---


gender in a sample consisting of 45 men and 55 women.

All we can say is that there are more females than males

--- Content provided by​ FirstRanker.com ---

in the sample or that 45% of the sample is male.



(2) Ordinal measurement. In ordinal measurement numerals,

--- Content provided by‌ FirstRanker.com ---


letters or other symbols are used to rank objects. This is

essentially an advances form of categorization. Objects in this

--- Content provided by‌ FirstRanker.com ---

measurement are classified not only as to whether they

share some characteristic with another object but also

whether they have more or less of this characteristics than

--- Content provided by⁠ FirstRanker.com ---


some other object on some characteristic. A significant

amount of marketing research, particularly consumer-

--- Content provided by‍ FirstRanker.com ---

oriented research, relies on this type of data. Their most

common use is in obtaining preferences measurements. For

example, a consumer or a sample of experts may be asked

--- Content provided by‍ FirstRanker.com ---


to rank preference for several brands, flavors, or package

designs. Attitude measures are also often ordinal in nature.

--- Content provided by⁠ FirstRanker.com ---



However, ordinal measurements do not provide information

on how much more or less of the characteristic various

--- Content provided by‍ FirstRanker.com ---


objects possess. For example, if in respect of a certain

characteristic two objects have the ranks 5 and 8 and two

--- Content provided by‍ FirstRanker.com ---

other objects the ranks 3 and 6, we cannot say that the

differences between the two pairs are equal. There is also

no way to know that any object has none of the

--- Content provided by‌ FirstRanker.com ---


characteristic being measured.



--- Content provided by​ FirstRanker.com ---


The king of descriptive statistics that can be calculated

from these data are mode, median and percentages. For

--- Content provided by‍ FirstRanker.com ---

example, in the following table which shows the quality

ratings given by 600 housewives to one brand of coffee

one can usefully calculate the median and modal quality

--- Content provided by FirstRanker.com ---


ratings. Both are 2` in this case. One can also calculate the

percentages of the total appearing in each rank. But it is

--- Content provided by FirstRanker.com ---

meaningless to calculate a mean because the differences

between ordinal scales values are not necessarily, the same.


--- Content provided by⁠ FirstRanker.com ---


Quality Rating

No. of respondents giving
rating

--- Content provided by‌ FirstRanker.com ---


1

200

--- Content provided by‍ FirstRanker.com ---

2

200

3

--- Content provided by FirstRanker.com ---


100

4

--- Content provided by⁠ FirstRanker.com ---

50

5

50

--- Content provided by⁠ FirstRanker.com ---




(2) Interval measurement. Interval measurements represent

--- Content provided by‍ FirstRanker.com ---

numerals to rank objects such that numerically equal

distances on the scale represent equal distances in the

property being measured. The distances between numerals

--- Content provided by‌ FirstRanker.com ---


are thus, very meaningful because, by comparing these

distances we can know how far apart the objects are with

--- Content provided by⁠ FirstRanker.com ---

respect to the property in question. For example, if we are

measuring the achievements of 4 students W, X, Y, and Z on

an interval scale and obtain the values 1, 4, 5 and 8

--- Content provided by FirstRanker.com ---


respectively ( as Shown below) then by comparing the

intervals, we can legitimately say that the difference

--- Content provided by FirstRanker.com ---

between W and Y in their achievements is the same as the


difference between X and Z and That the difference

--- Content provided by‍ FirstRanker.com ---

between X and Z is four times the difference between W

and Y.


--- Content provided by‌ FirstRanker.com ---



W X Y Z


--- Content provided by‍ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

0 1 2 3 4 5 6 7 8 9 10



One very important drawback of this measurement, however, is that We

--- Content provided by⁠ FirstRanker.com ---


cannot compare objects on the basis of ratios of their absolute scores.

Thus, in our example, we cannot say that the achievements of X is twice

--- Content provided by⁠ FirstRanker.com ---

as great as that of Z. The reason is that in our measurement the zero

point is arbitrary so that any change in this point will change the

absolute scores and the ratios between scores. For example, if the

--- Content provided by FirstRanker.com ---


arbitrary zero point of the above scale is shifted four scale-points

downward, the position of X and Z on the scale will change to 8 and 12

--- Content provided by‌ FirstRanker.com ---

and the previous ration of 1: 2 will now become 2:3

The most common examples of interval scales are the centigrade and

Fahrenheit temperature scales which start with different points of origin.

--- Content provided by⁠ FirstRanker.com ---


The point of origin (for the same natural phenomenon, the freezing point

of water) is zero on the Centigrade scale and 32 on Fahrenheit. Because

--- Content provided by⁠ FirstRanker.com ---

of this difference the ratio between any two readings on the Centigrade

scale (e.g., between 10 to 30) is not the same as that on the Fahrenheit

scale as shown below. One can only talk of a 20. C rise in temperature

--- Content provided by FirstRanker.com ---


but not of 30. C as being three times as hot as 10.C.



--- Content provided by​ FirstRanker.com ---

Centigrade 0 10 30 100

Fahrenheit 32 53 86 212


--- Content provided by​ FirstRanker.com ---


The most frequent of interval measurement in social sciences is index

numbers which are calculated on the basis of an arbitrary zero point.

--- Content provided by‍ FirstRanker.com ---

Another common form of interval measurement is a likert scale which is

used in the measurement of attitudes and personality.


--- Content provided by‌ FirstRanker.com ---

Virtually the entire range of statistical analysis can be applied to data

measured on interval scales. One can use such descriptive measures as

the mean, median, mode, range and standard deviation. Bivariate

--- Content provided by⁠ FirstRanker.com ---


correlation analysis, t-test, analysis of variance test, and most multivariate

techniques applied for purposes of drawing inferences can also be used.

--- Content provided by‌ FirstRanker.com ---



(4) Ratio measurement. This measurement, besides possessing the property

of the interval measurement, possesses one additional property , viz., it

--- Content provided by FirstRanker.com ---


has a true, natural or absolute zero point, one for which there is

universal agreement as to its location A true zero means that the object

--- Content provided by​ FirstRanker.com ---

measuring zero possesses none of the property in question. Height and

weight are obvious example. In general, wherever the objects, are being

counted` for possessing or not possessing a certain characteristic ratio

--- Content provided by FirstRanker.com ---


measurement is being done. In all such cases the number 0 has a true

meaning ? the object possesses none of the characteristic being measured.

--- Content provided by⁠ FirstRanker.com ---

Other common examples of this type of measurement are sales, costs,

number of purchasers, length, time, etc.

With a ratio measurement, the comparison between ratios of the absolute

--- Content provided by⁠ FirstRanker.com ---


magnitude of the numbers becomes possible. Thus, a person weighing

100kg . is said to be twice as heavy as one weighing 50kg. and a person

--- Content provided by‌ FirstRanker.com ---

weighing 150kg is three times as heavy. Further, with a ratio scale we can

compare intervals, rank objects according to magnitude, or use the


--- Content provided by​ FirstRanker.com ---

numbers to identify the objects. All descriptive measures and inferential

techniques are applicable to ratio-measured data.

The following table summaries the above discussion about four types of

--- Content provided by⁠ FirstRanker.com ---


measurement;



--- Content provided by⁠ FirstRanker.com ---

Types Of Measurement

Type

Basic empirical

--- Content provided by​ FirstRanker.com ---


Typical

Typical Statistics

--- Content provided by​ FirstRanker.com ---

operation

usage

Descriptive Inferential

--- Content provided by⁠ FirstRanker.com ---


1. Nominal

Determination

--- Content provided by⁠ FirstRanker.com ---

Classification

Percentage chi-square,

Of

--- Content provided by FirstRanker.com ---




equality

--- Content provided by‍ FirstRanker.com ---

(0, Male-female

Binomial test

1,2,..........9)

--- Content provided by FirstRanker.com ---


purchaser

non-

--- Content provided by‌ FirstRanker.com ---

purchaser, Team

A Team-B

2. Ordinal

--- Content provided by‌ FirstRanker.com ---


Determination

Rankings:

--- Content provided by FirstRanker.com ---

Median Rank-order

Of

greater

--- Content provided by‍ FirstRanker.com ---


or

less preference data, correletion

--- Content provided by​ FirstRanker.com ---

(o<1<2...........<9)

market position,

attitude measures,

--- Content provided by‌ FirstRanker.com ---


many

psychological

--- Content provided by‌ FirstRanker.com ---

measures

3. Interval Determination of equality Index

numbers, Mean, Range, Product-moment

--- Content provided by⁠ FirstRanker.com ---




of intervals (2-1=7-6)

--- Content provided by​ FirstRanker.com ---

attitude measures Standard



Determination of equality Sales,

--- Content provided by⁠ FirstRanker.com ---


units Deviation

4. Ratio

--- Content provided by FirstRanker.com ---

o f r

a t ios (2/4 = 4/8)

produced, number Geometric Coefficient of

--- Content provided by‌ FirstRanker.com ---


of

customers. variation

--- Content provided by‍ FirstRanker.com ---

Costs, age

mean


--- Content provided by​ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---


COMPONENTS OF MEASUREMENT

Ideally speaking there should be only one component of a measurement

--- Content provided by FirstRanker.com ---

and this component should be a direct reflection of the characteristic being

measured. Unfortunately, such a situation seldom exists. Very often, a

measurement consists of not one but two components- one representing the

--- Content provided by⁠ FirstRanker.com ---


influence of the characteristic being measured and the other representing

the influence of those characteristics which the researcher is not interested

--- Content provided by FirstRanker.com ---

in measuring but which still creep in against his wishes. The

characteristics are as follows:


--- Content provided by⁠ FirstRanker.com ---


1.

Additional stable characteristics of the object or event, for

--- Content provided by‍ FirstRanker.com ---

example, the respondent`s tendency to give only favorable

responses independent of his true feelings.

2.

--- Content provided by⁠ FirstRanker.com ---


Short-term characteristics of the object, for example, fatigue,

health, hunger, and emotional state.

--- Content provided by​ FirstRanker.com ---

3.

Situational characteristics, for example, the presence or absences

or some other person or of location under which the

--- Content provided by‍ FirstRanker.com ---


measurement is taken

4.

--- Content provided by‌ FirstRanker.com ---

Characteristics of the measurement process, for example, Gender,

age, and ethnic background. In addition, style of dress of the

interviewer or the method of interviewing-telephone, mail,

--- Content provided by FirstRanker.com ---


personal interview, etc.

5.

--- Content provided by⁠ FirstRanker.com ---

Characteristics of the measuring instruments, for example,

unclear instructions, ambiguous questions, confusing terms,

omitted questions, etc.

--- Content provided by‌ FirstRanker.com ---


6.

Characteristics of the response process, for example, mistakes

--- Content provided by⁠ FirstRanker.com ---

caused by checking a wrong responses


7.

--- Content provided by FirstRanker.com ---

Characteristics of the analysis, for example, mistakes caused by

wrong coding, tabulating, etc.


--- Content provided by​ FirstRanker.com ---


Six out of these seven characteristics (2 to 7) give rise to variable errors

in a measurement, i.e., errors which occur randomly each time something

--- Content provided by FirstRanker.com ---

is measured. First characteristics gives rise to a systematic error, i.e., error

that occurs in a consistent manner each time something is measured. It is

also caleed bias. Thus, the general situation is:

--- Content provided by‌ FirstRanker.com ---


M=C+VE+SE where M stands for the measurement , C stands for the

characteristic being measured, VE stands, for variable errors and SE

--- Content provided by FirstRanker.com ---

stands for systematic errors.



ACCURACY MEASUREMENT

--- Content provided by‍ FirstRanker.com ---


Accuracy of measurement depends upon the extent to which it is free

from systematic and variable errors. Freedom from variable errors is

--- Content provided by‍ FirstRanker.com ---

known as the reliability of a measurement and freedom from systematic

errors is known as the validity of a measurement. Reliability and Validity

every researcher to know how they are measured.

--- Content provided by​ FirstRanker.com ---


The Measurement Process

The following are the steps involved in the measurement process

--- Content provided by‍ FirstRanker.com ---

1. Identifying the concept of interest

2. Development of a construct

3. A constitutive definition

--- Content provided by‍ FirstRanker.com ---


4. Operational definition

5. Measurement scales

--- Content provided by FirstRanker.com ---


6. Evaluating reliability and validity of the scale

7. utilization of scale

--- Content provided by⁠ FirstRanker.com ---

8. Research findings

We shall discuss the four numerical scales such as Nominal Scale, Ordinal scale,

interval scale and ratio scale, functions of measurement and measurement error,

--- Content provided by​ FirstRanker.com ---


benefits of measurement as described below.

Nominal Level of Measurement

--- Content provided by⁠ FirstRanker.com ---

a. Nominal Scales

i. Partitions data into categories that is mutually exclusive

and collectively exhaustive. Examples

--- Content provided by FirstRanker.com ---


ii. Gender:

(1) Male (2) Female

--- Content provided by⁠ FirstRanker.com ---

iii. Geographic Area:

(1) Urban (2) Rural (3) Suburban(4) Semi-urban

Ordinal Scales

--- Content provided by‍ FirstRanker.com ---


b. Used strictly to indicate rank order.

Ranking

--- Content provided by FirstRanker.com ---

Please rank the following brands of Colour Television from 1-5 with 1 being the

most and 5 the least preferred

Samsung________ LG_______

--- Content provided by​ FirstRanker.com ---



Thomson ________

BPL _______

--- Content provided by‌ FirstRanker.com ---


Videocon ________

? Interval Scales

--- Content provided by FirstRanker.com ---

? Contains all the features of ordinal scales

? Added dimension that the intervals between the data

points on the scale are equal.

--- Content provided by‍ FirstRanker.com ---


? Ratio Scales

? All powers of those mentioned as well as a meaningful

--- Content provided by‍ FirstRanker.com ---

absolute zero or origin.

? Accurate Data Imply Accurate Measurement

M = A + E

--- Content provided by‌ FirstRanker.com ---


Where M = measurement

A = accuracy

--- Content provided by FirstRanker.com ---

E = errors-random or systematic

Nominal Scale

Nominal Scale is defined as measurement of a variable which results in the

--- Content provided by⁠ FirstRanker.com ---


classification of phenomena into a set of consistent and non-overlapping

attributes (yes, no, male, female, etc.). Nonparametric statistics: Tests of

--- Content provided by⁠ FirstRanker.com ---

significance that require few assumptions about the population. Use of these

statistics should occur when samples are small (fewer than 30 subjects), when

subjects were not randomly sampled, or data are not interval level. ...

--- Content provided by‍ FirstRanker.com ---





A nominal scale allows for the classification and labeling of elements or

--- Content provided by‌ FirstRanker.com ---


objects into mutually exclusive and exhaustive categories based on defined

features.

--- Content provided by​ FirstRanker.com ---

A scale of measurement with two or more categories that have no numerical

(less than, greater than) properties. Proportion of map distance to ground

distance at a point or line

--- Content provided by​ FirstRanker.com ---


Nominal Data

Classification data, e.g. male/ female

--- Content provided by‍ FirstRanker.com ---

No ordering, e.g. it makes no sense to state that

Female >Male

Arbitrary labels, e.g., male/female, 0/1, etc

--- Content provided by‍ FirstRanker.com ---


Nominal Scale. We can examine if a nominal scale data is equal to some

particular value or to count the number of occurrences of each value. For

--- Content provided by‍ FirstRanker.com ---

example, gender is a nominal scale variable. We could examine if the gender

of a person is Female or to count the number of males in a sample.

At the first level of measurement, numbers are used to classify data. In fact,

--- Content provided by FirstRanker.com ---


words or letters would be equally appropriate. For example when we wanted

to classify a cricket team into left footed and right footed players, we

--- Content provided by⁠ FirstRanker.com ---

could put all the left footed players into a group classified as 1 and all the

right footed players into a group as 2.


--- Content provided by FirstRanker.com ---

The only mathematical or statistical operation that can be performed on

nominal scales is a frequency run or count. We cannot determine an average,

except for the mode ? that number which holds the most responses -, nor can

--- Content provided by‌ FirstRanker.com ---


we add and subtract numbers.

The purpose of this set of notes is to briefly summarize several aspects of

--- Content provided by‌ FirstRanker.com ---

scales of measurement including:

(a) the measurement principle involved for each scale,

(b) examples of the measurement scales,

--- Content provided by‍ FirstRanker.com ---


(c) permissible arithmetic operations for each scale, and

(d) examples of statistics that are appropriate for each scale.

--- Content provided by‍ FirstRanker.com ---

People or objects with the same scale value are the same on some attribute.

The values of the scale have no 'numeric' meaning in the way that you

usually think about numbers. People or objects with a higher scale value

--- Content provided by⁠ FirstRanker.com ---


have more of some attribute.

The intervals between adjacent scale values are indeterminate. Scale

--- Content provided by‌ FirstRanker.com ---

assignment is by the property of "greater than," "equal to," or "less than."

Intervals between adjacent scale values are equal with respect the the

attribute being measured.

--- Content provided by FirstRanker.com ---


E.g., the difference between 8 and 9 is the same as the difference between 76

and 77.

--- Content provided by‌ FirstRanker.com ---

There is a rationale zero point for the scale.


Ratios are equivalent, e.g., the ratio of 2 to 1 is the same as the ratio of 8 to

--- Content provided by⁠ FirstRanker.com ---

4.

Each "higher" level of measurement includes the measurement principle of

the "lower" level of measurement. For example, the numbers 8 and 9 in an

--- Content provided by‌ FirstRanker.com ---


interval scale indicate that the object assigned a 9 has more of the attribute

being measured than does the object assigned an 8 (ordinal property) and

--- Content provided by FirstRanker.com ---

that all persons assigned a 9 have equivalent amounts of the attribute being

measured (nominal property). This also implies that you can do lower level

statistics on higher-level measurement scales.

--- Content provided by⁠ FirstRanker.com ---


Guttmann Scales

For thinking about numeric types, measurement, truth, social structures

--- Content provided by‍ FirstRanker.com ---

.Fiske argues that all social life is composed of patterns of interaction that

are based on four types of scale: categorical, ordinal, interval, and ratio. The

scales provide ways of perceiving, and thereby of organizing social

--- Content provided by⁠ FirstRanker.com ---


interaction. The four scales are not mere manifestations of a single culture,

but are different primary mathematical structures. They are different

--- Content provided by‍ FirstRanker.com ---

axiomatically. They are Trans cultural. In 1944, Louis Guttmann pointed out

that all forms of measurement belong to one of four types of scale:

categorical, ordinal, interval, and ratio.

--- Content provided by‌ FirstRanker.com ---


Why is Level of Measurement Important?

First, knowing the level of measurement helps us to decide how to interpret the

--- Content provided by⁠ FirstRanker.com ---

data from that variable. When we know that a measure is nominal then we know

that the numerical values are just short codes for the longer names. Second,


--- Content provided by​ FirstRanker.com ---

knowing the level of measurement helps us to decide what statistical analysis is

appropriate on the values that were assigned.

In nominal measurement, the numerical values just "name" the attribute

--- Content provided by‍ FirstRanker.com ---


uniquely. No ordering of the cases is implied. For example, the numerical

numbers in football team l are measures at the nominal level. A player with

--- Content provided by FirstRanker.com ---

number 7 is not more of anything than a player with number 5.

In ordinal measurement, the attributes can be rank-ordered. Here, distances

between attributes do not have any meaning. For example, on a survey you

--- Content provided by‍ FirstRanker.com ---


might code Educational Qualification as 0=less than Higher .Secondary

1=Higher .Secondary. 2=Under Graduate degree; 3=Post Graduate degree;

--- Content provided by⁠ FirstRanker.com ---

4=professional degree; 5=doctoral degree . In this measure, higher numbers

mean more education. But is distance from 0 to 1 same as 3 to 4? Of course not.

The interval between values is not interpretable in an ordinal measure.

--- Content provided by⁠ FirstRanker.com ---


In interval measurement the distance between attributes does have meaning. For

example, when we measure temperature (in Fahrenheit), the gap between 30 and

--- Content provided by⁠ FirstRanker.com ---

40 is same as gap between 70 and 80. The interval between values is

interpretable. Because of this, it makes sense to compute an average of an

interval variable, where it doesn't make sense to do so for ordinal scales. But we

--- Content provided by‍ FirstRanker.com ---


should note that in interval measurement ratios don't make any sense - 80

degrees is not twice as hot as 40 degrees (although the attribute value is twice as

--- Content provided by​ FirstRanker.com ---

large).

Finally, in ratio measurement there is always an absolute zero that is

meaningful. This means that we could construct a meaningful fraction (or ratio)

--- Content provided by⁠ FirstRanker.com ---


with a ratio variable. Weight is a ratio variable. In applied business research,

most "count" variables are ratio, for example, the number of clients in past six

--- Content provided by⁠ FirstRanker.com ---


months. Because we could have zero clients and because it is meaningful to

say that "...we had twice as many clients in the past six months as we did in the

--- Content provided by FirstRanker.com ---

previous six months."


The categories of the variable:

--- Content provided by⁠ FirstRanker.com ---

have

an

inherent are

--- Content provided by FirstRanker.com ---


numbers are numbers that

are

--- Content provided by FirstRanker.com ---

order

with

have

--- Content provided by‍ FirstRanker.com ---


a

Level

--- Content provided by FirstRanker.com ---

names

from more to less equal intervals theoretical
or higher to lower

--- Content provided by‌ FirstRanker.com ---

between them

zero point

Nominal X

--- Content provided by‌ FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---



level
Ordinal X

--- Content provided by​ FirstRanker.com ---

X




--- Content provided by⁠ FirstRanker.com ---


level
Interval X

X

--- Content provided by‌ FirstRanker.com ---


X



--- Content provided by‍ FirstRanker.com ---

level
Ratio

X

--- Content provided by‍ FirstRanker.com ---

X

X

X

--- Content provided by‍ FirstRanker.com ---


level

Source: Prof Candance Clark, social statistics

--- Content provided by‌ FirstRanker.com ---

It's important to recognize that there is a hierarchy implied in the level of

measurement idea. At lower levels of measurement, assumptions tend to be less

restrictive and data analyses tend to be less sensitive. At each level up the

--- Content provided by⁠ FirstRanker.com ---


hierarchy, the current level includes all of the qualities of the one below it and

adds something new. In general, it is desirable to have a higher level of

--- Content provided by​ FirstRanker.com ---

measurement (e.g., interval or ratio) rather than a lower one (nominal or

ordinal).

Functions of Measurement

--- Content provided by‌ FirstRanker.com ---


? Standardization

? Sharpen arguments and distinctions

--- Content provided by⁠ FirstRanker.com ---

? Enhance the precision of statements


? Allow application of mathematics

--- Content provided by​ FirstRanker.com ---

Causality

Ultimately, we seek to establish causal relationships among the phenomena we

study. Necessary condition for causality: one that must be present for an event to

--- Content provided by⁠ FirstRanker.com ---


occur, although its presence does not guarantee occurrence; its absence

guarantees nonoccurrence.

--- Content provided by​ FirstRanker.com ---

Sufficient condition for causality: one that guarantees that the event will occur

whenever it is present; but the event may still occur in its absence .

Ideal outcome of a scientific study - a set of conditions that are simultaneously

--- Content provided by​ FirstRanker.com ---


necessary and sufficient for an event that would truly explain the event .The

classic scientific technique for establishing causality is the controlled

--- Content provided by​ FirstRanker.com ---

experiment. Social experiments rarely achieve the same kind of controlled

conditions that are obtainable in a laboratory.

The cause must precede the effect in time.

--- Content provided by‍ FirstRanker.com ---


The two variables must be empirically correlated. Otherwise stated as:

association is a necessary condition for causality. The correlation between the

--- Content provided by FirstRanker.com ---

two variables cannot be explained by the existence of a third variable. We could

find out the cause and effect relationships. Correlation does not equal causality.

Causal attributions always involve an interpretation that is relative to the

--- Content provided by FirstRanker.com ---


categories and understandings of mechanisms available when the study is

written. Causal inferences are based on assumptions. Human actions and

--- Content provided by FirstRanker.com ---

interactions are rarely so simple that a single source of causality can be

identified. Social science theories do help to provide possible explanations of

tendencies or actions of groups with common characteristics. Yet there is always

--- Content provided by​ FirstRanker.com ---


a possibility of alternative inferences. Even assuming that some common set of

explanations could be identified among selected subjects, are they representative

--- Content provided by FirstRanker.com ---

of the whole population? The standard of acceptability for any experimental or

observational evidence is: can someone else replicate the process such that the

same results are produced.

--- Content provided by​ FirstRanker.com ---


Survey research is one of the most important areas of measurement in applied

business research. The broad area of survey research encompasses any

--- Content provided by‍ FirstRanker.com ---

measurement procedures that involve asking questions of respondents. A

"survey" can be anything from a short paper-and-pencil feedback form to an

intensive one-on-one in-depth interview.

--- Content provided by‌ FirstRanker.com ---


Summary

In the early 1940`s, the Harvard psychologist S.S. Stevens coined the terms

--- Content provided by FirstRanker.com ---

nominal, ordinal, interval, and ratio to describe a hierarchy of measurement

scales used in psychophysics, and classified statistical procedures according to

the scales for which they were permissible. Measurement may be defined as

--- Content provided by‍ FirstRanker.com ---


the assignment of numerals to characteristics of objects , persons, states, or

events, according to rules. What is measured is not the objects, person,

--- Content provided by‌ FirstRanker.com ---

state, or event itself but some characteristic of it. When objects are

counted, for example, we do not measure the object itself but only its

characteristic of being present. We never measure people, only their age,

--- Content provided by‌ FirstRanker.com ---


height, weight, or some other characteristic. There are four levels of

measurement: nominal, ordinal, interval and ratio.

--- Content provided by FirstRanker.com ---



KEY TERMS

Measurement

--- Content provided by​ FirstRanker.com ---


Nominal scale

Ordinal scale

--- Content provided by‍ FirstRanker.com ---

Interval scale

Ratio scale


--- Content provided by⁠ FirstRanker.com ---


QUESTIONS FOR REVIEW

1. Define: Measurement

--- Content provided by‍ FirstRanker.com ---

2. What are the steps involved in the Measurement Process.

Define the following: Nominal scale, Ordinal scale, Interval scale and Ratio

scale

--- Content provided by FirstRanker.com ---


3. Indicate whether each of the following measures uses a nominal scale,

ordinal scale, Interval scale and ratio scale.

--- Content provided by⁠ FirstRanker.com ---

a. Prices of commodities

b. Married and unmarried

c. Employed and unemployed

--- Content provided by​ FirstRanker.com ---


d. Professorial rank Professor, Associate Professor, Assistant professor.

4. What are the characteristics of Measurement?

--- Content provided by​ FirstRanker.com ---

5. What do you mean by the term Measurement error?

Further Reference

1. William G.Zigmand, 2003, Business Research Methods, Thompson Asia pvt

--- Content provided by⁠ FirstRanker.com ---


ltd.,

2.D.D.Sharma , Marketing research,1999,SultanChand&Sons

--- Content provided by‍ FirstRanker.com ---

3. Cooper, DonaldR, Schindler, Pamela.s 2006 Businees Research Methods

4.P.C.Tripathi,2005.A

Text

--- Content provided by⁠ FirstRanker.com ---


Book

of

--- Content provided by⁠ FirstRanker.com ---

Research

Methodology,

SultanChand&Sons.

--- Content provided by‌ FirstRanker.com ---



5.O.R.Krishnaswami,M.Ranganatham,2005.Methodology of Research in Social

Sciences,Himalaya Publishing House,Mumbai.

--- Content provided by​ FirstRanker.com ---



Unit-IV

DATA INSTRUMENTS

--- Content provided by‌ FirstRanker.com ---




LEARNING OBJECTIVES

--- Content provided by FirstRanker.com ---

After reading this chapter , you should be able to understand

Features of a research instrument.
Types of research instruments.
Selection of research instrument for the study.

--- Content provided by⁠ FirstRanker.com ---


INTRODUCTION
In today's unpredictable business environment, customer behavior and attitudes

are changing, the economy is shifting, stakeholders are demanding, and the

--- Content provided by‍ FirstRanker.com ---


competition is getting fierce. Business firms can capitalize these changes by

conducting marketing research. And good marketing research leads to great

--- Content provided by​ FirstRanker.com ---

ideas that build business results. The foundation of good research is good data.

Traditionally, the term Marketing Research evokes images of huge volumes of

data collected by armies of interviewers. And the same images always involve

--- Content provided by​ FirstRanker.com ---


data relating exclusively to responses to marketing initiatives, advertising,

pricing, new product launches etc., Perhaps there might be some awareness of

--- Content provided by⁠ FirstRanker.com ---

data on Customer Satisfaction and Retention.

There are very few hard and fast rules to define the task of data collection. Each

research project uses a data collection technique appropriate to the particular

--- Content provided by‌ FirstRanker.com ---


research methodology. The two primary goals for both quantitative and

qualitative studies are to boost response and maximize accuracy. To adequately

--- Content provided by​ FirstRanker.com ---

address the research questions a variety of data collection methods and

instruments will be used. These methods and instruments are not specific to any


--- Content provided by‍ FirstRanker.com ---

one question but provide data that when used in combinations will address the

research questions. In general researcher can opt for any instrument or

combinations of various instruments for the study chosen.

--- Content provided by FirstRanker.com ---


i) TYPE OF INSTRUMENTS

Data instruments are the instruments employed by the researcher to collect the

--- Content provided by FirstRanker.com ---

required data. Data collection instruments are designed to collect standard

information from a large number of study participants. After deciding which

type of information is needed, the methods of accessing data must be

--- Content provided by⁠ FirstRanker.com ---


determined. There are different methods of collecting data. The actual design of

the instrument, the data collection form that is used to ask and record the

--- Content provided by‌ FirstRanker.com ---

information is critical to the success of the research. Based on the objectives of

the study researcher can design the instruments or forms to gather the data. The

questionnaire is an example of research instrument, in an observation based

--- Content provided by‍ FirstRanker.com ---


study, the instrument can also be a mechanical or electronic device of

observation like Tape recorder and camera. Survey methods may include mailed

--- Content provided by⁠ FirstRanker.com ---

questionnaires, telephone interviews, or face-to-face interviews. Information

gathered may be qualitative as well as quantitative. In experimental types of

research some times an observation device is used, some times a questionnaire is

--- Content provided by​ FirstRanker.com ---


used.

DATA COLLECTION INSTRUMENTS

--- Content provided by​ FirstRanker.com ---

a. Questionnaires
b. Interview schedule
c. Observational / Scanning tools
d. Archival Data Collection Tools
e. Interviews / Focus Group Protocols

--- Content provided by⁠ FirstRanker.com ---

f. Experimentation
g. Multi-Modal Data Collection



--- Content provided by FirstRanker.com ---

a. Questionnaires :


Questionnaire is a common instrument for collecting data beyond the physical

--- Content provided by​ FirstRanker.com ---

reach of the researcher, that is, from a large size sample of people. It is an

impersonal instrument for collecting information and must, therefore, contain

clear questions, worded as simply as possible to avoid any confusion or

--- Content provided by​ FirstRanker.com ---


ambiguity since the researcher probably will not be present to explain what was

meant by any one particular question. Questionnaires are an inexpensive way to

--- Content provided by‍ FirstRanker.com ---

gather data from a potentially large number of respondents. Often they are the

only feasible way to reach a number of reviewers large enough to allow

statistically analysis of the results. A well-designed questionnaire that is used

--- Content provided by‌ FirstRanker.com ---


effectively can gather information on both the overall performance of the test

system as well as information on specific components of the system. If the

--- Content provided by FirstRanker.com ---

questionnaire includes demographic questions on the participants, they can be

used to correlate performance and satisfaction with the test system among

different groups of users.

--- Content provided by​ FirstRanker.com ---


It is important to remember that a questionnaire should be viewed as a multi-

stage process beginning with definition of the aspects to be examined and

--- Content provided by​ FirstRanker.com ---

ending with interpretation of the results. Every step needs to be designed

carefully because the final results are only as good as the weakest link in the

questionnaire process. Although questionnaires may be cheap to administer

--- Content provided by⁠ FirstRanker.com ---


compared to other data collection methods, they are every bit as expensive in

terms of design time and interpretation.

--- Content provided by⁠ FirstRanker.com ---

b. Interview schedule:

Interview schedule is a set of questions prepared by the researcher to conduct

the survey through personal contact. The research worker or enumerator fills the

--- Content provided by​ FirstRanker.com ---


schedule. With respect to primary research, the foremost tool is the personal

interview. The face-to-face contact between researcher and respondent is not

--- Content provided by​ FirstRanker.com ---

equal in terms of the potential quality of data that can be obtained. In the face-

to-face interview it is possible to record more than the verbal responses of the

interviewee, which are often superficial. When human beings communicate

--- Content provided by FirstRanker.com ---


directly with each other much more information is communicated between them.

When two people face one another, the dialogue is conducted on several levels.

--- Content provided by‌ FirstRanker.com ---

It goes beyond verbal expression. The nature of words used, facial expressions

and body language all communicate what the other party means.


--- Content provided by​ FirstRanker.com ---


c. Observational / Scanning tools:

Tools used to guide visual inspection and documentation of characteristics of

--- Content provided by​ FirstRanker.com ---

people or settings of interest. The scanning process can include recording

observations in writing or using checklists, videotaping, or other methods.

Scanning processes may be supplemented by interviews, surveys, and other

--- Content provided by⁠ FirstRanker.com ---


techniques.

d. Archival Data Collection Tools :

--- Content provided by‌ FirstRanker.com ---

Forms or other procedures designed to collect or abstract data from existing

records for research or evaluation purposes. Sometimes called indicator` data,

examples of archival data sources include program files and records from

--- Content provided by​ FirstRanker.com ---


student life programs, academic administration, social services agencies, police,

courts, or other community-based agencies.

--- Content provided by​ FirstRanker.com ---

e. Interviews / Focus Group Protocols:

A set of questions and procedures designed to guide one-on-one or group

interviews. Procedures fall on a continuum from unstructured, in which the

--- Content provided by​ FirstRanker.com ---


questions are used as a general guide, to very structured, in which the questions

are asked word-for-word in a set order.

--- Content provided by FirstRanker.com ---

f. Experimentation:

The popularity of experimentation in marketing research has much to do with

the possibilities of establishing cause and effect. Experiments can be configured

--- Content provided by⁠ FirstRanker.com ---


in such a way as to allow the variable causing a particular effect to be isolated.

Other methods commonly used in marketing research, like surveys, provide

--- Content provided by‍ FirstRanker.com ---

much more ambiguous findings. In fact, experimentation is the most scientific

method employed in marketing research

g. Multi-Modal Data Collection

--- Content provided by⁠ FirstRanker.com ---


Many clients require more than one method of data collection to optimally

execute their research. An example of this is a very complex survey that would

--- Content provided by​ FirstRanker.com ---

be cost prohibitive on the telephone, but would be easy to complete on paper.

Reaching the respondent by different roots certainly increases the response rate.

Construction of a good data instrument

--- Content provided by‍ FirstRanker.com ---


In general researcher designs the instrument catering to the nature of the study

and other environment. The following points may be considered for constructing

--- Content provided by​ FirstRanker.com ---

a good instrument

Reliability of the instrument .
Relevancy
Brevity

--- Content provided by‌ FirstRanker.com ---

Nonambiguity
Specificity
Test the validity of the data.
unbiased reply.
Cost effective.

--- Content provided by FirstRanker.com ---

Possibility of pre-test .



ii) STEPS INVOLVED IN DESIGNING DATA INSTRUMENT

--- Content provided by‌ FirstRanker.com ---




Data collection tools plays vital role in research. They serve two very important

--- Content provided by⁠ FirstRanker.com ---

purposes. Firstly it helps the researcher to identify varies elements required to

address for achieving the objectives of the study. Secondly it roots for how data


--- Content provided by⁠ FirstRanker.com ---

should be collected. While preparing the instrument due importance must be

given to the environment. Companies desire and background of the respondent

are to be considered for improving the effectives of the selected method. Many

--- Content provided by‍ FirstRanker.com ---


researchers elect to use instruments that were used previously by other

researchers. An advantage of the strategy is that information about reliability

--- Content provided by‍ FirstRanker.com ---

and validity of the instruments may be established already. Instruments often

have been revised many times and are designed to facilitate easy data collection.

Disadvantages to using existing instruments are that the instruments may not

--- Content provided by FirstRanker.com ---


have been used with the populations to be studied or may not address a

particular issue .The following steps can be used to design a data instrument.

--- Content provided by‌ FirstRanker.com ---

1. Decide what information is needed

2. Know the environment

3. Decide what method to use

--- Content provided by⁠ FirstRanker.com ---


4. Format the instrument

5. Pilot test

--- Content provided by FirstRanker.com ---

6. Get feedback on the instrument

7. Revise


--- Content provided by​ FirstRanker.com ---


IV.B. DATA COLLECTION METHODS



--- Content provided by FirstRanker.com ---

In marketing research collection of data plays a dominant role. Data is required

to make decision in any business situation. the researcher is faced with one of

the most difficult problems of obtaining suitable, accurate and adequate data. As

--- Content provided by⁠ FirstRanker.com ---


soon as the research design has been decide, the next step is that of selecting the

sources of data. Based on the nature and purpose of the study researcher can go

--- Content provided by FirstRanker.com ---

for various modes of data collection .Data sources can be classified into two

categories namely primary and secondary sources .Discussion about sources are

as follows.

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---


TYPES OF DATA



--- Content provided by​ FirstRanker.com ---





PRIMARY

--- Content provided by‌ FirstRanker.com ---


SECONDARY



--- Content provided by‍ FirstRanker.com ---



INTERNAL

EXTERNAL

--- Content provided by FirstRanker.com ---


INTERNAL

EXTERANL

--- Content provided by‌ FirstRanker.com ---

SOURCES

SOURCES


--- Content provided by‌ FirstRanker.com ---


SOURCES

SOURCES

--- Content provided by‌ FirstRanker.com ---





INTERVIEW

--- Content provided by​ FirstRanker.com ---


CENSES /

SURVEY/

--- Content provided by‍ FirstRanker.com ---



COMPANY

PERIODICAL AND

--- Content provided by‍ FirstRanker.com ---


KEY PEOPLE

INTERVIEW

--- Content provided by FirstRanker.com ---

RECORDS

REPORTS

OBSERVATIO

--- Content provided by​ FirstRanker.com ---




N

--- Content provided by​ FirstRanker.com ---






--- Content provided by FirstRanker.com ---


IV.B. a. COLLECTION OF SECONDARY DATA

OR

--- Content provided by FirstRanker.com ---

DESK RESEARCH

Secondary data is data which has been collected by individuals or agencies for

purposes other than those of their particular research study. These secondary

--- Content provided by​ FirstRanker.com ---


data source may also be termed as paper source. These secondary sources could

include previous research reports, newspaper, magazine and journal content,

--- Content provided by​ FirstRanker.com ---

government and NGO statistics. Sometimes secondary research is required in

the preliminary stages of research to determine what is known already and what

new data are required, or to inform research design. At other times, it may make

--- Content provided by​ FirstRanker.com ---


be the only research technique used. For example, if a government department

has conducted a survey of, say, family medical expenditures, and then medicine

--- Content provided by FirstRanker.com ---

manufacturer might use this data in the organization`s evaluations of the total

potential market for a new product. Similarly, statistics prepared by a ministry of

health will prove useful to a whole host of people and organizations, including

--- Content provided by‌ FirstRanker.com ---


those marketing medicine supplies.



--- Content provided by FirstRanker.com ---

i).THE NATURE OF SECONDARY SOURCES OF INFORMATION

No marketing research study should be undertaken without a prior search of

secondary sources (also termed desk research). There are several grounds for

--- Content provided by FirstRanker.com ---


making such a bold statement.

1. Secondary data may be available which is entirely appropriate and

--- Content provided by FirstRanker.com ---

wholly adequate to draw conclusions and answer the question or

solve the problem.

2. It is far cheaper to collect secondary data than to obtain primary

--- Content provided by‌ FirstRanker.com ---


data. For the same level of research budget a thorough examination

of secondary sources can yield a great deal more information than

--- Content provided by‌ FirstRanker.com ---

can be had through a primary data collection exercise.

3. The time involved in searching secondary sources is much less than

that needed to complete primary data collection.

--- Content provided by‌ FirstRanker.com ---


4. Secondary sources of information can yield more accurate data than

that obtained through primary research. This is not always true but

--- Content provided by‌ FirstRanker.com ---

where a government or international agency has undertaken a large

scale survey, or even a census, this is likely to yield far more

accurate results than custom designed and executed surveys when

--- Content provided by​ FirstRanker.com ---


these are based on relatively small sample sizes.

5. It should not be forgotten that secondary data can play a substantial

--- Content provided by‌ FirstRanker.com ---

role in the exploratory phase of the research when the task at hand is

to define the research problem and to generate hypotheses.


--- Content provided by‍ FirstRanker.com ---

6. Secondary sources help define the population. Secondary data can be

extremely useful both in defining the population and in structuring

the sample to be taken. For instance, government statistics on a

--- Content provided by FirstRanker.com ---


country's agriculture will help decide how to stratify a sample and,

once sample estimates have been calculated, these can be used to

--- Content provided by⁠ FirstRanker.com ---

project those estimates to the population.



ii). CLASSIFICATION OF SECONDARY DATA

--- Content provided by​ FirstRanker.com ---




The sources of secondary data can be classified into four categories. They are:

--- Content provided by‍ FirstRanker.com ---

1. Published sources: data available from various national and international

institutions

2. Unpublished sources: in few cases data maintained by the organizations are

--- Content provided by‍ FirstRanker.com ---


not available to the public/researchers in published forms. Researchers can get

this information through personal contacts.

--- Content provided by FirstRanker.com ---

3. Internal source: internal data are prepared by summaries of companies

internal operations. Sales report, invoice, shipment records and consumer

database maintained by the companies are the major sources.

--- Content provided by‌ FirstRanker.com ---


4. External data: which means data collected from outside of the company.

Collection of external data is more complex because the data have much

--- Content provided by​ FirstRanker.com ---

greater variety and the sources are more.



Sources of secondary data

--- Content provided by​ FirstRanker.com ---


Trade associations

National and local press Industry magazines

--- Content provided by‌ FirstRanker.com ---

National/ international governments


Informal contacts

--- Content provided by​ FirstRanker.com ---

Trade directories

Published company accounts

Business libraries

--- Content provided by​ FirstRanker.com ---


Professional institutes and organizations

Omnibus surveys

--- Content provided by FirstRanker.com ---

Previously gathered marketing research

Census data

Public records

--- Content provided by​ FirstRanker.com ---


Web sites



--- Content provided by⁠ FirstRanker.com ---

Government publications: Official statistics are statistics collected by

governments and their various agencies, bureaus, and departments. These

statistics can be useful to researchers because they are an easily obtainable and

--- Content provided by FirstRanker.com ---


comprehensive source of information that usually covers long periods of time.

However, because official statistics are often characterized by unreliability,

--- Content provided by‌ FirstRanker.com ---

data gaps, over-aggregation, inaccuracies, mutual inconsistencies, and lack of

timely reporting, it is important to critically analyze official statistics for

accuracy and validity. There are several reasons why these problems exist:The

--- Content provided by FirstRanker.com ---


scale of official surveys generally requires large numbers of enumerators

(interviewers) and, in order to reach those numbers enumerators contracted are

--- Content provided by‌ FirstRanker.com ---

often under-skilled. The size of the survey area and research team usually

prohibits adequate supervision of enumerators and the research process; and

resource limitations (human and technical) often prevent timely and accurate

--- Content provided by‌ FirstRanker.com ---


reporting of results.

Technical Reports: Technical reports are accounts of work done on research

--- Content provided by⁠ FirstRanker.com ---

projects. They are written to provide research results to colleagues, research


institutions, governments, and other interested researchers. A report may come

--- Content provided by FirstRanker.com ---

from completed research or on-going research projects.

Scholarly Journals: Scholarly journals generally contain reports of original

research or experimentation written by experts in specific fields. Articles in

--- Content provided by‌ FirstRanker.com ---


scholarly journals usually undergo a peer review where other experts in the

Same field review the content of the article for accuracy, originality, and

--- Content provided by‍ FirstRanker.com ---

relevance.

Literature Review Articles: Literature review articles assemble and review

original research dealing with a specific topic. Reviews are usually written by

--- Content provided by​ FirstRanker.com ---


experts in the field and may be the first written overview of a topic area.

Review articles discuss and list all the relevant publications from which the

--- Content provided by​ FirstRanker.com ---

information is derived.

Trade Journals: Trade journals contain articles that discuss practical

information concerning various fields. These journals provide people in these

--- Content provided by​ FirstRanker.com ---


fields with information pertaining to that field or trade.

Syndicate: The growing demand for marketing data has produced a number of

--- Content provided by FirstRanker.com ---

companies that collect and sell standardized data designed to serve information

needs shared by a number of organization; the most common are information

needs associated with performance-monitoring research. Syndicated data

--- Content provided by‍ FirstRanker.com ---


sources can be classified as

1. Consumer data-collected from consumers regarding purchases.

--- Content provided by FirstRanker.com ---

2. Retail data-focus on products or services sold through retailers .

3. Wholesale data- report on movement of different brands .

4. Industrial data-data on companies to construct sales prospect

--- Content provided by‌ FirstRanker.com ---


5. Advertising evaluation data- to measure the effectiveness of the

advertisement

--- Content provided by‍ FirstRanker.com ---

6. Media and audience data- to match market and media


Reference Books: Reference books provide secondary source material. In many

--- Content provided by‌ FirstRanker.com ---

cases, specific facts or a summary of a topic is all that is included. Handbooks,

manuals, encyclopedias, and dictionaries are considered reference books .

International publications: The United Nations Organizations(UNO),

--- Content provided by‌ FirstRanker.com ---


International

Labor

--- Content provided by‍ FirstRanker.com ---

Organization(ILO),International

Monetary

Fund(IMF),World Bank, etc., are publishing numerous items of data relating to

--- Content provided by‌ FirstRanker.com ---


the socio-economic conditions of different countries.

iii). QUALITY OF INFORMATION SOURCES

--- Content provided by‌ FirstRanker.com ---

One of the advantages of secondary data review and analysis is that individuals

with limited research training or technical expertise can be trained to conduct

this type of analysis. Key to the process, however, is the ability to judge the

--- Content provided by‍ FirstRanker.com ---


quality of the data or information that has been gathered. The following tips

will help you to assess the quality of the data.

--- Content provided by​ FirstRanker.com ---

Determine the Original Purpose of the Data Collection: Consider the

purpose of the data or publication. Is it a government document or statistic, data

collected for corporate and/or marketing purposes, or the output of a source

--- Content provided by‍ FirstRanker.com ---


whose business is to publish secondary data (e.g., research institutions).

Ascertain the Credentials of the Source(s) or Author(s) of the Information :

--- Content provided by‌ FirstRanker.com ---

What are the author`s or source`s credentials -- educational background, past

works/writings, or experience -- in this area?

Are the methods sound?: Does the article have a section that discusses the

--- Content provided by‍ FirstRanker.com ---


methods used to conduct the study? If it does not, you can assume that it is a

popular audience publication and should look for additional supporting

--- Content provided by​ FirstRanker.com ---

information or data.

Date of Publication : When was the source published? Is the source current or

out-of-date? Topic areas of continuing or rapid development, such as the

--- Content provided by⁠ FirstRanker.com ---


sciences, demand more current information.


Who is the Intended Audience? Is the publication aimed at a specialized or a

--- Content provided by​ FirstRanker.com ---


general audience? Is the source too elementary -- aimed at the general public?

What is the Coverage of the Report or Document? Does the work update

--- Content provided by‍ FirstRanker.com ---

other sources, substantiate other materials/reports that you have read, or add new

information to the topic area?

After judging the competency of the data based on the above tests, researcher

--- Content provided by‍ FirstRanker.com ---


can chose the right one.

SECONDARY DATA

--- Content provided by​ FirstRanker.com ---

ADVANTAGES

DISADVANTAGES

1. Low cost

--- Content provided by​ FirstRanker.com ---


1. Lack of consistency of

2. speed

--- Content provided by​ FirstRanker.com ---

perspective

3. Often the only resource, for

2. Biases and inaccuracies can

--- Content provided by⁠ FirstRanker.com ---


example historical

not be checked

--- Content provided by⁠ FirstRanker.com ---

documents

3. Published statistics often

4. Only way to examine

--- Content provided by‍ FirstRanker.com ---


raise more questions than

large-scale trends

--- Content provided by‌ FirstRanker.com ---

they answer (for example,

5. Saves time

what does church

--- Content provided by‌ FirstRanker.com ---


6. Wide range of availability

attendance tells us about

--- Content provided by‌ FirstRanker.com ---

7. Serves as a source of

religious beliefs?)

comparative data

--- Content provided by FirstRanker.com ---


4. The concern over whether



--- Content provided by‍ FirstRanker.com ---

any data can be totally

separated from the context

of its collection

--- Content provided by‌ FirstRanker.com ---




Marketing Research Agencies in India

--- Content provided by FirstRanker.com ---

Operations Research Group (ORG)

National Council of Applied Economic Research (NCAER)


--- Content provided by​ FirstRanker.com ---

Indian Market Research Bureau (IMRB)

Marketing and Research Group (MARG)

Marketing Research and Advisory Services (MRAS)

--- Content provided by⁠ FirstRanker.com ---


Marketing and Business Associate (MBA)



--- Content provided by FirstRanker.com ---

IV.B.b. COLLECTION OF PRIMARY DATA

Primary data is data collected for the first time. It is original and collected for a

specific purpose, or to solve a specific problem. It is expensive, and time

--- Content provided by FirstRanker.com ---


consuming, but is more focused than secondary research. There are many ways

to conduct primary ( data collection) research. The following are the prime

--- Content provided by‍ FirstRanker.com ---

methods:

1. Observation

2. Questionnaire

--- Content provided by​ FirstRanker.com ---


3. Interview

4. Focus groups

--- Content provided by FirstRanker.com ---

5. Projective techniques

6. Product tests

7. Diaries

--- Content provided by FirstRanker.com ---


8. Omnibus Studies

9. Clinics

--- Content provided by‍ FirstRanker.com ---

10. Surveys

11. Case study


--- Content provided by⁠ FirstRanker.com ---


I-OBSERVATION METHODS



--- Content provided by⁠ FirstRanker.com ---


Observation involves the process of physically or mechanically recording some

specific aspect of a consumer`s activity or behavior .Observational techniques

--- Content provided by​ FirstRanker.com ---

are methods by which an individual or individuals gather firsthand data on

programs, processes, or behaviors being studied. They provide evaluators with

an opportunity to collect data on a wide range of behaviors, to capture a great

--- Content provided by‍ FirstRanker.com ---


variety of interactions, and to openly explore the evaluation topic. By directly

observing operations and activities, the evaluator can develop a holistic

--- Content provided by‍ FirstRanker.com ---

perspective, i.e., an understanding of the context within which the project

operates. This may be especially important where it is not the event that is of

interest, but rather how that event may fit into, or be impacted by, a sequence of

--- Content provided by​ FirstRanker.com ---


events. Observational approaches also allow the evaluator to learn about things

the participants or staff may be unaware of or that they are unwilling or unable

--- Content provided by‌ FirstRanker.com ---

to discuss in an interview or focus group.

When to use observations. Observations can be useful during both the

formative and summative phases of evaluation. For example, during the

--- Content provided by‌ FirstRanker.com ---


formative phase, observations can be useful in determining whether or not the

project is being delivered and operated as planned. In the hypothetical project,

--- Content provided by‍ FirstRanker.com ---

observations could be used to describe the faculty development sessions,

examining the extent to which participants understand the concepts, ask the right

questions, and are engaged in appropriate interactions. Some research designs

--- Content provided by FirstRanker.com ---


call for this type of data. Some contented that observation is objective than

communication .How ever , observation whether in a field setting or a

--- Content provided by⁠ FirstRanker.com ---

laboratory setting ,is not very versatile.

Recording Observational Data

Observations are carried out using a carefully developed set of steps and

--- Content provided by FirstRanker.com ---


instruments. The observer is more than just an onlooker, but rather comes to the


scene with a set of target concepts, definitions, and criteria for describing events.

--- Content provided by‍ FirstRanker.com ---


While in some studies observers may simply record and describe, in the majority

of evaluations, their descriptions are, or eventually will be, judged against a

--- Content provided by FirstRanker.com ---

continuum of expectations.

Observations usually are guided by a structured protocol. The protocol can take

a variety of forms, ranging from the request for narrative describing events seen

--- Content provided by⁠ FirstRanker.com ---


to a checklist or a rating scale of specific behaviors/activities that address the

evaluation question of interest. The use of a protocol helps assure that all

--- Content provided by​ FirstRanker.com ---

observers are gathering the pertinent information and, with appropriate training,

applying the same criteria in the evaluation .The protocol goes beyond a

recording of events, i.e., use of identified materials, and provides an overall

--- Content provided by‌ FirstRanker.com ---


context for the data. The protocol should prompt the observer to,

Describe the setting of program delivery, i.e., where the observation

--- Content provided by⁠ FirstRanker.com ---

took place and what the physical setting was like;

Identify the people who participated in those activities, i.e.,

characteristics of those who were present;

--- Content provided by FirstRanker.com ---


Describe the content of the intervention, i.e., actual activities and

messages that were delivered;

--- Content provided by​ FirstRanker.com ---

Document the interactions between implementation staff and project

participants;

Describe and assess the quality of the delivery of the intervention; and

--- Content provided by⁠ FirstRanker.com ---


Be alert to unanticipated events that might require refocusing one or

more evaluation questions.

--- Content provided by‌ FirstRanker.com ---

METHODS OF OBSERVATION

There are several methods of observation of which any one or a combination of

some of them can be used by the observer.

--- Content provided by‍ FirstRanker.com ---


1. Structured-unstructured observation:


Structured observation is used when the research problem has been formulated

--- Content provided by​ FirstRanker.com ---


precisely and the observers have been told specifically what is to be observed.

They may be given a simple form to record their observations. Unstructured

--- Content provided by FirstRanker.com ---

observation implies that observers are free to observe what ever they think is

relevant and important .While structured observations are free from subjective

bias, unstructured observations are subject to this limitation .The extent of the

--- Content provided by FirstRanker.com ---


bias may vary to the extent an observation is unstructured.

2. Disguised-undisguised observation:

--- Content provided by⁠ FirstRanker.com ---

In the case of disguised observation, the subjects do not know that they are

being observed. In some cases, disguised observation may be made by the

observer by posing as one of the shoppers who are being observed. This type of

--- Content provided by‍ FirstRanker.com ---


observation is often preferred because it is feared that people may behave

differently when they know they are being observed. It may be difficult to

--- Content provided by FirstRanker.com ---

completely disguise an observation, though this apart, it poses an ethical

question of its desirability when those who are being observed are kept in the

dark.

--- Content provided by⁠ FirstRanker.com ---


3. Observation under natural setting-laboratory setting:

Observations can also be classified on the bases of their setting, i.e. natural or

--- Content provided by⁠ FirstRanker.com ---

laboratory. Observations in field studies are in their natural setting and are,

therefore undertaken in extremely realistic conditions. Sometimes, an

experimental manipulation may be introduced in a field study. Observation in a

--- Content provided by⁠ FirstRanker.com ---


laboratory setting, on the other hand, enables the observer to control extraneous

variables which influence the behavior of people. Observational studies in

--- Content provided by‍ FirstRanker.com ---

laboratory settings have certain advantages over field studies. They enable the

collection of data promptly and economically and in addition, permit the use of

more objective measurements.

--- Content provided by⁠ FirstRanker.com ---


4. Direct-indirect observation:


In the case of direct observation, the event or the behavior of a person is to be

--- Content provided by FirstRanker.com ---


observed as it occurs .In contrast; indirect observation implies that some record

of past behavior is observed. In other words ,the behavior itself is not observed

--- Content provided by⁠ FirstRanker.com ---

,rather its effects are observed. An observer engaged in indirect observation

generally looks for physical traces of behavior or occurrence of an event.

Suppose he is interested in knowing about the liquor consumption of a

--- Content provided by⁠ FirstRanker.com ---


household, he would like for empty liquor bottles in the garbage. Similarly, the

observer may seek the permission of the housewife to see the pantry. He may

--- Content provided by‌ FirstRanker.com ---

carry a pantry audit to ascertain the consumption of certain types of products. It

may be noted that the success of an indirect observation largely depends on how

best the observer is able to identify physical traces of the problem under study.

--- Content provided by‍ FirstRanker.com ---


Direct observation is far more common than indirect observation.

5. Human-mechanical observation:

--- Content provided by⁠ FirstRanker.com ---

Another way of classifying observations is whether they are made manually or

by machines. Most of the studies in marketing research based on human

observation wherein trained observers are required to observe and faithfully

--- Content provided by‍ FirstRanker.com ---


record their observations. In some cases, mechanical devices such as eye

cameras and audiometers are use for observation. One of the major advantages

--- Content provided by​ FirstRanker.com ---

of electrical/mechanical devices is that their recordings are free from subjective

bias. As against this advantage, such observations may be less valid than human

observations. This is because the observer`s power of integration can lead to a

--- Content provided by‌ FirstRanker.com ---


more valid evaluation of the observation.

OBSERVATIONS

--- Content provided by‌ FirstRanker.com ---

ADVANTAGES

DISADVANTAGES


--- Content provided by‌ FirstRanker.com ---





1. Expensive and time consuming

--- Content provided by‌ FirstRanker.com ---


1. Provide direct information about

2. Need well-qualified, highly trained

--- Content provided by‍ FirstRanker.com ---

behavior of individuals and groups

observers; may need to be content


--- Content provided by FirstRanker.com ---


experts

2. Permit evaluator to enter into and

--- Content provided by​ FirstRanker.com ---

3. May affect behavior of participants

understand situation/context

4. Selective perception of observer

--- Content provided by‍ FirstRanker.com ---




may distort data

--- Content provided by‌ FirstRanker.com ---

3. Provide good opportunities for

5. Investigator has little control over

identifying unanticipated outcomes

--- Content provided by‌ FirstRanker.com ---


situation



--- Content provided by FirstRanker.com ---

6. Behavior or set of behaviors

4. Exist in natural, unstructured, and

observed may be unusual

--- Content provided by‌ FirstRanker.com ---


flexible setting



--- Content provided by‍ FirstRanker.com ---



II-QUESTIONNAIRE METHOD OF DATA

COLLECTION

--- Content provided by‍ FirstRanker.com ---




This method of data collection is quite popular, particularly in case of big

--- Content provided by⁠ FirstRanker.com ---

enquiries. It is being adopted by private individuals, research workers, private

and public organizations and even by governments. In this method a

questionnaire is sent (usually by post) to the persons concerned with a request to

--- Content provided by‌ FirstRanker.com ---


answer the questions and return the questionnaire. A questionnaire consists of a

number of questions written or printed in a definite order on a form or set of

--- Content provided by‌ FirstRanker.com ---

forms. The questionnaire is send to respondents who are expected to read and

understand the questions and write down the reply in the space meant for the

purpose in the questionnaire itself. The respondents have to answer the questions

--- Content provided by FirstRanker.com ---


on their own. The method of collecting data by mailing the questionnaire to


respondents is most extensively employed in various economic and business

--- Content provided by FirstRanker.com ---


surveys.

The merits claimed on behalf of this method are as follows:

--- Content provided by​ FirstRanker.com ---

1. There is low cost even when the universe is large and is widely spread

geographically.

2. It is free from the bias of the interviewer; answers are in respondent`s

--- Content provided by FirstRanker.com ---


own words.

3. Respondents have adequate time to give well thought out answers.

--- Content provided by⁠ FirstRanker.com ---

4. Respondents, who are not easily approachable, can also be reached

conveniently.

5. Large samples can be made use of and thus results can be made more

--- Content provided by​ FirstRanker.com ---


dependable and reliable.

The major demerits of this system are listed here:

--- Content provided by‍ FirstRanker.com ---

Low rate of return of the duly filled in questionnaire; bias due to no-response is

often indeterminate.

1. It can be used only when respondents are educated and cooperating.

--- Content provided by⁠ FirstRanker.com ---


2. The control over questionnaire may be lost once it is sent.

3. There is inbuilt inflexibility because of the difficulty of amending the

--- Content provided by‌ FirstRanker.com ---

approach once questionnaire have been dispatched.

4. There is also the possibility of ambiguous replies or omission of replies

altogether to certain questions; interpretation of omissions is difficult.

--- Content provided by FirstRanker.com ---


5. It is difficult to know whether willing respondents are truly

representative.

--- Content provided by‌ FirstRanker.com ---

6. This method is likely to be the slowest of all.

Before using this method, it is always advisable to conduct pilot study` (Pilot

Survey) for testing the questionnaires.

--- Content provided by FirstRanker.com ---


Main aspects of questionnaire:


Quite often questionnaire is considered as the heart of a survey operation. Hence

--- Content provided by⁠ FirstRanker.com ---


it should be very carefully constructed. If it is not properly set up, then the

survey is bound to fail. This fact requires us to study the main aspects of a

--- Content provided by‍ FirstRanker.com ---

questionnaire viz., the general form, question sequence and question formulation

and wording. Researcher should note the following with regard to these three

main aspects of a questionnaire:

--- Content provided by FirstRanker.com ---


1. General form:

structured questionnaire.

--- Content provided by‍ FirstRanker.com ---

unstructured questionnaire.

So far as the general form of a questionnaire is co concerned it can either be

structured or unstructured questionnaire. Structured questionnaires are those

--- Content provided by FirstRanker.com ---


questionnaires in which there are definite, concrete and pre-determined

questions. The questions are presented with exactly the same wording and in the

--- Content provided by‌ FirstRanker.com ---

same order to all respondents. Structured questions may also have fixed

alternative questions in which responses of the informants are limited to the

stated alternatives. Thus a highly structured questionnaire is one in which all

--- Content provided by​ FirstRanker.com ---


questions and answers are specified and comments in the respondent`s own

words are held to the minimum. When these characteristics are not present in a

--- Content provided by‍ FirstRanker.com ---

questionnaire, it can be termed as unstructured or non-structured questionnaire.

2. Question sequence:

In order to make questionnaire effective and to ensure quality to the replies

--- Content provided by‍ FirstRanker.com ---


received, a researcher should pay attention to the question-sequence in preparing

the questionnaire. A proper sequence of questions reduces considerably the

--- Content provided by FirstRanker.com ---

chances of individual questions being misunderstood. The question-sequence

must be clear and smoothly-moving, meaning thereby the relation of one

question to another should be readily apparent to the respondent, with questions

--- Content provided by‌ FirstRanker.com ---


that are easiest to answer being put in the beginning. The first few questions are

particularly important because they are likely to influence the attitude of the

--- Content provided by‍ FirstRanker.com ---

respondent and in seeking his human interest. The following type of questions

should be generally avoided as opening questions in the questionnaire:

o Questions that put too great a strain on the memory or intellect of the

--- Content provided by FirstRanker.com ---


respondent.

o Questions of a personal character.

--- Content provided by‌ FirstRanker.com ---

o Questions related to personal wealth etc,

Following the opening questions, we should have questions that are really vital

to research problem and a connecting thread should run through successive

--- Content provided by​ FirstRanker.com ---


questions. Ideally, the question-sequence should conform to the respondent`s

way of thinking.

--- Content provided by‍ FirstRanker.com ---

2. Question formulation and wording:

With regard to this aspect of questionnaire, the researcher should note that each

question must be very clear for any sort of misunderstanding can do irreparable

--- Content provided by​ FirstRanker.com ---


harm to survey. Question should also be impartial in order not to give a biased

picture of the true state of affairs. Questions should be constructed with a view

--- Content provided by FirstRanker.com ---

to their forming a logical part of a well thought out tabulation plan. In general all

questions should meet the following standards :

(a) Should be easily understood.

--- Content provided by⁠ FirstRanker.com ---


(b) Should be simple i.e., should convey only one thought at a time.

(c) Should be concrete and should conform as much as possible to the

--- Content provided by FirstRanker.com ---

respondent`s ways of thinking.

4. Kind of questions:

Open end question (format)

--- Content provided by‍ FirstRanker.com ---

Closed-end question

In general, there are two types of questions one will ask, open format or closed

format. Open format questions are those that ask for unprompted opinions. In

--- Content provided by‍ FirstRanker.com ---


other words, there are no predetermined set of responses, and the participant is

free to answer however he chooses. Open format questions are good for

--- Content provided by⁠ FirstRanker.com ---

soliciting. An obvious advantage is that the variety of responses should be wider

and more truly reflect the opinions of the respondents. This increases the

likelihood of you receiving unexpected and insightful suggestions, for it is

--- Content provided by FirstRanker.com ---


impossible to predict the full range of opinion. It is common for a questionnaire

to end with and open format question asking the respondent for her unabashed

--- Content provided by​ FirstRanker.com ---

ideas for changes or improvements.

Open format questions have several disadvantages. First, their very nature

requires them to be read individually. There is no way to automatically tabulate

--- Content provided by‍ FirstRanker.com ---


or perform statistical analysis on them. This is obviously more costly in both

time and money, and may not be practical for lower budget or time sensitive

--- Content provided by⁠ FirstRanker.com ---

evaluations. They are also open to the influence of the reader, for no two people

will interpret an answer in precisely the same way. This conflict can be

eliminated by using a single reader, but a large number of responses can make

--- Content provided by FirstRanker.com ---


this impossible



--- Content provided by​ FirstRanker.com ---

Finally, open format questions require more thought and time on the part of the

respondent. Whenever more is asked of the respondent, the chance of tiring or

boring the respondent increases.

--- Content provided by‍ FirstRanker.com ---


Closed format questions usually take the form of a multiple-choice question.

They are easy for the respondent, There is no clear consensus on the number of

--- Content provided by‍ FirstRanker.com ---

options that should be given in an closed format question. Obviously, there

needs to be sufficient choices to fully cover the range of answers but not so

many that the distinction between them becomes vague.

--- Content provided by⁠ FirstRanker.com ---


Qualities of a Good Question:

There are good and bad questions. The qualities of a good question are as

--- Content provided by‍ FirstRanker.com ---

follows:

1. Questions should evoke the truth.


--- Content provided by​ FirstRanker.com ---

2. Asks for an answer on only one dimension.

3. Can accommodate all possible answers.

4. Don`t imply a desired answer.

--- Content provided by​ FirstRanker.com ---


5. Don`t use emotionally loaded or vaguely defined words.

6. Don`t ask the respondent to order or rank a series of more than few

--- Content provided by‌ FirstRanker.com ---

items.



III-INTERVIEW METHODS OF DATA COLLECTION

--- Content provided by‍ FirstRanker.com ---




This is the technique most associated with marketing research. An interview is a

--- Content provided by‌ FirstRanker.com ---

specialized type of communication, usually verbal, between two or more people

and is carried out for a specific purpose. It is different from an ordinary

conversation in that its form and purpose is structured. Interviews can be

--- Content provided by⁠ FirstRanker.com ---


telephone, face-to-face, or over the Internet. The use of interviews as a data

collection method begins with the assumption that the participants` perspectives

--- Content provided by FirstRanker.com ---

are meaningful, knowable, and able to be made explicit, and that their

perspectives affect the success of the project. An interview, rather than a paper

and pencil survey, is selected when interpersonal contact is important and when

--- Content provided by FirstRanker.com ---


opportunities for follow-up of interesting comments are desired.

Generally two types of interviews are used in marketing research: structured

--- Content provided by‌ FirstRanker.com ---

interviews, in which a carefully worded questionnaire is administered; and in-

depth interviews, in which the interviewer does not follow a rigid form. In the

former, the emphasis is on obtaining answers to carefully phrased questions.

--- Content provided by​ FirstRanker.com ---


Interviewers are trained to deviate only minimally from the question wording to

ensure uniformity of interview administration. In the latter, however, the

--- Content provided by​ FirstRanker.com ---

interviewers seek to encourage free and open responses, and there may be a


tradeoff between comprehensive coverage of topics and in-depth exploration of

--- Content provided by⁠ FirstRanker.com ---

a more limited set of questions.

PREPARING FOR INTERVIEWS

If you are going to carry out an interview, you need to think about the steps

--- Content provided by‌ FirstRanker.com ---


involved. Good preparation must be done before the interview to make sure that

you get what you need from it, and some thought given afterwards to the

--- Content provided by FirstRanker.com ---

information gathered. The following steps can be followed for conducting the

interview

1. Decide on the purpose of the interview:

--- Content provided by FirstRanker.com ---


Clear understanding of the purpose of the interview will definitely enhances

the efficiency of the method. Before throwing questions the researchers

--- Content provided by​ FirstRanker.com ---

themselves must sure of their motto. For example, Are you trying to find out

someone's opinion about something? Are you trying to help someone with a

problem? , are you interviewing someone for a job?

--- Content provided by⁠ FirstRanker.com ---


2. Decide what kind of information you need to get from the interview to

achieve the purpose:

--- Content provided by‍ FirstRanker.com ---

Every interview must be preplanned to ensure the desired outcome and to use

time efficiently. Begin with an opening statement of purpose, goals, timing,

confidentiality, and format. The researcher may have a list of specific goals.

--- Content provided by​ FirstRanker.com ---


When the interview is conducted to study the level of customer satisfaction, the

parameters must be specifically selected.

--- Content provided by‌ FirstRanker.com ---

3. Decide what questions you are going to ask:

Researcher should draw up a list of questions so that the answers help to achieve

the goals. Before selecting interviewing as a data collection method, the

--- Content provided by​ FirstRanker.com ---


researcher must determine whether the research question can be answered

appropriately by interviewing people who have experienced the phenomenon of

--- Content provided by‍ FirstRanker.com ---

interest. A hypothetical study will be used to illustrate one process the

researcher could use to facilitate interviewing.

4. Carry out the interview:

--- Content provided by​ FirstRanker.com ---


Starting of an interview it self an art, the approaches used by the researcher

heavily influences the respondent in the way of answering. Spend a little time

--- Content provided by​ FirstRanker.com ---

setting the scene and getting acquainted with the interviewee (ice breaker) will

certainly open the mind of the respondent. Giving assurance to the respondent

about confidentiality and criticism positively increases the reliability.

--- Content provided by FirstRanker.com ---


5. Study the answers to the questions: The closing of the interview is very

important. Researcher must ensure that the answers heard are the answers that

--- Content provided by⁠ FirstRanker.com ---

were given. Restate the answers and get acceptance from the interviewee. Allow

clarification of any misstatements or misunderstandings. Give reassurance of the

purpose of the interview being data collection not oversight. Share any

--- Content provided by FirstRanker.com ---


suggestions for improvement if considered advisable Before completing the

interview the researcher make sure that , whether the goals have been achieved

--- Content provided by FirstRanker.com ---

or not. If not, uncovered areas are to be identified and enough time must be

asked from the respondent to continue the interview.


--- Content provided by FirstRanker.com ---






--- Content provided by FirstRanker.com ---

6. Make a decision about the purpose of the interview:

As soon as the interview is over if possible , the out come of the interview may

be reported to the respondent. In marketing research for various reasons this

--- Content provided by‌ FirstRanker.com ---


may not be advisable.

The role of the interviewer:

--- Content provided by‌ FirstRanker.com ---

The interviewer is really the "jack-of-all-trades" in marketing. The interviewer's

role is complex and multifaceted. The researcher must posse`s capability of

extracting the answer from the respondent .In most cases they are the backbone

--- Content provided by‍ FirstRanker.com ---



of the functioning of the interview. To perform the task the following things are

essential:

--- Content provided by‍ FirstRanker.com ---


1. Locate and enlist cooperation of respondents

2. Motivate respondents to do good job

--- Content provided by‌ FirstRanker.com ---

3. Clarify any confusion/concerns

4. Observe quality of responses

5. Conduct a good interview

--- Content provided by​ FirstRanker.com ---


TYPES OF INTERVIEW

a. Telephone interviews

--- Content provided by FirstRanker.com ---

Telephone ownership is very common in developed countries. It is ideal for

collecting data from a geographically dispersed sample. The interviews tend to

be very structured and tend to lack depth. Telephone interviews are cheaper to

--- Content provided by​ FirstRanker.com ---


conduct than face-to-face interviews (on a per person basis).

Advantages of telephone interviews

--- Content provided by‌ FirstRanker.com ---

1. Phone interviews can have a shorter data collection period than face-

to-face interviews.

2. Phone interviews may have a better response rate .

--- Content provided by FirstRanker.com ---

3. Phone interview reduces travel costs while permitting interaction

with remote participants.

4. Phone interviews can supplement site visits, face-to-face interviews,

--- Content provided by FirstRanker.com ---


and other methods. For example, after a site visit or a survey you
could gather additional data by conducting a phone interview

5. Cheaper than face-to-face interviews

--- Content provided by​ FirstRanker.com ---


Disadvantages of telephone interviews

1. Phone interviews can be quite tiring, so they are often shorter than

--- Content provided by​ FirstRanker.com ---

face-to-face interviews.

2. Phone interviews can be difficult if the interviewer or interviewee

has a strong accent.

--- Content provided by⁠ FirstRanker.com ---


3. Phone interviews are not as good as face-to-face interviews when

you are dealing with complex issues.

--- Content provided by⁠ FirstRanker.com ---

4. If you have multiple interviewers, you have to worry about consistent

approaches to the interviews.


--- Content provided by‍ FirstRanker.com ---

5. Phone interviews are often conducted at times that are convenient to

the participant, but not for the interviewer (evenings, early mornings,
weekends)

--- Content provided by FirstRanker.com ---

6. Phone interviews at a person`s office or home can involve many

potential distractions like colleagues stopping by, calls on other lines,
background noise, and the lure of using the computer to work during
the phone interview.

--- Content provided by‍ FirstRanker.com ---


7. Respondents can simply hang up
8. Interviews tend to be a lot shorter
9. Visual aids cannot be used
10. Researchers cannot see the behavior or body language of the

--- Content provided by⁠ FirstRanker.com ---


rspondet.



--- Content provided by⁠ FirstRanker.com ---

b. Face-to-face interviews

When marketers want to discuss questions in great depth, they generally use

personal interview, which are face-to-face interviews conducted with one

--- Content provided by‍ FirstRanker.com ---


person or a group of people at one time. personal interviews can be large and

more detailed than other types of study. The research will probe and develop

--- Content provided by‍ FirstRanker.com ---

points of interest.

Advantages of face-to-face interviews

1. They allow more 'depth'

--- Content provided by‍ FirstRanker.com ---

2. Physical prompts such as products and pictures can be used
3. Body language can emphasize responses
4. Respondents can be 'observed' at the same time

Disadvantages of face-to-face interviews

--- Content provided by‌ FirstRanker.com ---


1. Interviews can be expensive
2. It can take a long period of time to arrange and conduct.
3. Some respondents will give biased responses when face-to-face with

--- Content provided by‍ FirstRanker.com ---

a researcher.

c. In-depth interviews

An in-depth interview is a dialogue between a skilled interviewer and an

--- Content provided by FirstRanker.com ---


interviewee. Its goal is to detailed material that can be used in analysis. Such

interviews are best conducted face to face, although in some situations telephone

--- Content provided by FirstRanker.com ---


interviewing can be successful. Extensive probing and open-ended questions

characterize In-depth interviews. Typically, the project evaluator prepares an

--- Content provided by FirstRanker.com ---

interview guide that includes a list of questions or issues that are to be explored

and suggested probes for following up on key topics.

ADVANTAGES AND DISADVANTAGES OF IN-DEPTH INTERVIEW

--- Content provided by‌ FirstRanker.com ---


Advantages

Disadvantages

--- Content provided by​ FirstRanker.com ---

Usually yield richest data,

Expensive

and

--- Content provided by​ FirstRanker.com ---


time-

details, new insights

--- Content provided by FirstRanker.com ---

consuming

Permit face-to-face contact

Need well-qualified, highly

--- Content provided by FirstRanker.com ---


with respondents

trained interviewers

--- Content provided by‌ FirstRanker.com ---

Provide opportunity to

Interviewee may distort

explore topics in depth

--- Content provided by FirstRanker.com ---


information through recall

Afford

--- Content provided by⁠ FirstRanker.com ---

ability

to

error, selective perceptions,

--- Content provided by​ FirstRanker.com ---


experience the affective as

desire to please interviewer

--- Content provided by⁠ FirstRanker.com ---

well as cognitive aspects of

Flexibility can result in

responses

--- Content provided by‍ FirstRanker.com ---


inconsistencies

across

--- Content provided by​ FirstRanker.com ---

Allow

interviewer

to

--- Content provided by‌ FirstRanker.com ---


interviews

explain or help clarify

--- Content provided by⁠ FirstRanker.com ---

Volume of information too

questions, increasing the

large; may be difficult to

--- Content provided by⁠ FirstRanker.com ---


likelihood

of

--- Content provided by FirstRanker.com ---

useful

transcribe and reduce data

responses

--- Content provided by⁠ FirstRanker.com ---


Allow interviewer to be

flexible in administering
interview to

--- Content provided by‍ FirstRanker.com ---


particular

individuals

--- Content provided by‌ FirstRanker.com ---

or

circumstances

d. Computer Direct Interviews

--- Content provided by⁠ FirstRanker.com ---


These are interviews in which the Interviewees enter their own answers directly

into a computer. They can be used at malls, trade shows, offices, and so on. The

--- Content provided by‍ FirstRanker.com ---

Survey System's optional Interviewing Module and Interview Stations can easily

create computer-direct interviews. Some researchers set up a Web page survey

for this purpose.

--- Content provided by​ FirstRanker.com ---



Advantages

1. The virtual elimination of data entry and editing costs.

--- Content provided by​ FirstRanker.com ---

2. You will get more accurate answers to sensitive questions.
3. The elimination of interviewer bias. Different interviewers can ask

questions in different ways, leading to different results. The
computer asks the questions the same way every time.

--- Content provided by‌ FirstRanker.com ---


4. Ensuring skip patterns are accurately followed. The Survey System

can ensure people are not asked questions they should skip based on
their earlier answers. These automatic skips are more accurate than

--- Content provided by⁠ FirstRanker.com ---

relying on an Interviewer reading a paper questionnaire.

5. Response rates are usually higher. Computer-aided interviewing is

still novel enough that some people will answer a computer interview

--- Content provided by‍ FirstRanker.com ---

when they would not have completed another kind of interview.

Disadvantages

1. The Interviewees must have access to a computer or one must be

--- Content provided by⁠ FirstRanker.com ---


provided for them.

2. As with mail surveys, computer directs interviews may have serious

--- Content provided by​ FirstRanker.com ---

response rate problems in populations of lower educational and
literacy levels. This method may grow in importance as computer use
increases.


--- Content provided by FirstRanker.com ---


IV-FOCUS GROUPS

Focus groups are made up from a number of selected respondents based together

--- Content provided by‍ FirstRanker.com ---

in the same room. Highly experienced researchers work with the focus group to

gather in depth qualitative feedback. Groups tend to be made up from 10 to 18

participants. Discussion, opinion, and beliefs are encouraged, and the research

--- Content provided by‍ FirstRanker.com ---


will probe into specific areas that are of interest to the company commissioning

the research.

--- Content provided by​ FirstRanker.com ---

Typically focus groups are used as a means of testing concepts, new products,

and messages. A focus group is qualitative research, which means that you do

not obtain results with percentages, statistical testing, or tables. Instead, this

--- Content provided by⁠ FirstRanker.com ---


methodology is less structured than surveys or other quantitative research and

tends to be more exploratory as well. Rather than providing quantifiable

--- Content provided by⁠ FirstRanker.com ---


responses to a specific question obtained from a large sampling of the

population, focus group participants provide a flow of input and interaction

--- Content provided by FirstRanker.com ---

related to the topic or group of topics that the group is centered around. While

they appear to be less formal than a survey, focus groups do provide an

important source of information for making business decisions. It is important,

--- Content provided by​ FirstRanker.com ---


however, to ensure that persons using the results of such a qualitative study

understand how to correctly interpret the resulting information.

--- Content provided by‍ FirstRanker.com ---

Quantitative research provides results that can be generalized to a specific

population, because it is based on a statistical sampling of the target population.

The results of qualitative research, such as focus groups, however, are not

--- Content provided by‌ FirstRanker.com ---


quantifiable. They reflect only a very small segment of the target market in

question. Given the number of focus group participants, results are not

--- Content provided by⁠ FirstRanker.com ---

necessarily representative of the general population from which participants are

recruited and should not be considered as such.

When to Use and When to Avoid Focus Groups

--- Content provided by‍ FirstRanker.com ---


Focus groups are best used when the concept or idea you wish to evaluate is new

and when the best evaluation comes from letting the target customer (who can

--- Content provided by‌ FirstRanker.com ---

be either a consumer or a customer in the business-to-business sense) view the

concept directly. A good example of this is a new advertising campaign.

Typically, an advertising agency will want to test a new advertisement with the

--- Content provided by‌ FirstRanker.com ---


consumers it hopes to reach with the campaign. The agency needs to know

whether the message is clear, whether consumers view the advertisement

--- Content provided by FirstRanker.com ---

positively or negatively, whether the advertisement would prompt them to

purchase the product, and so forth. The agency can explore these questions by

showing the advertisement to consumers and discussing their reactions and their

--- Content provided by⁠ FirstRanker.com ---


likes and dislikes. Their comments will allow the agency to fine-tune the

advertisement or, if it is not well liked, to go back to the drawing board.

--- Content provided by‍ FirstRanker.com ---



Another common use of focus group research is product concept testing.

Participants in a group can discuss detailed diagrams and product descriptions,

--- Content provided by‌ FirstRanker.com ---


or they may test a product prototype in a hands-on fashion. This allows

researchers to identify customer needs and, attitudes regarding a concept before

--- Content provided by​ FirstRanker.com ---

investing in further product development.

A focus group study also is often used to design the questionnaire for a

quantitative survey. The focus group covers general issues on a topic, and

--- Content provided by FirstRanker.com ---


respondents' comments often help researchers identify pertinent issues that

might otherwise be left out of a survey. Hypotheses generated by focus groups

--- Content provided by⁠ FirstRanker.com ---

frequently lead to further testing using quantitative methods. Alternatively,

focus groups can be used to further interpret quantitative research. For example,

if a telephone survey produces a significant percentage of unexpected comments

--- Content provided by⁠ FirstRanker.com ---


on a certain topic, a focus group study could investigate the issue with greater

depth.

--- Content provided by‍ FirstRanker.com ---

Another particularly useful application of focus group research is as a

brainstorming mechanism. If you have a problem to solve, this type of

methodology often provides fresh insights regarding the issue at hand. It can

--- Content provided by⁠ FirstRanker.com ---


also provide an excellent forum for generating creative ideas or new-product

ideas for new markets, as well as generating new ideas for your established

--- Content provided by⁠ FirstRanker.com ---

markets.

Focus groups can be used for the following purposes

To test new concepts

--- Content provided by​ FirstRanker.com ---


To position a product/ service

To assess product usability

--- Content provided by‍ FirstRanker.com ---

To evaluate advertising/ copy

To evaluate promotions

To develop questionnaires

--- Content provided by FirstRanker.com ---


To generate ideas or support brainstorming


V. PROJECTIVE TECHNIQUES

--- Content provided by⁠ FirstRanker.com ---




The technique of inferring a subjects attitudes or values based on his or her

--- Content provided by FirstRanker.com ---

description of vague objects requiring interpretation. Projective techniques are

borrowed from the field of psychology. They will generate highly subjective

qualitative data. There are many examples of such approaches including: Inkblot

--- Content provided by⁠ FirstRanker.com ---


tests - look for images in a series of inkblots Cartoons - complete the 'bubbles'

on a cartoon series Sentence or story completion Word association - depends on

--- Content provided by FirstRanker.com ---

very quick (subconscious) responses to words .Psychodrama - Imagine that you

are a product and describe what it is like to be operated, warn, or used.

Projective techniques consist of the following:

--- Content provided by⁠ FirstRanker.com ---


a. Word association tests: In word association test the subject is presented

with a list of words, one at a time, and asked to respond with first that

--- Content provided by‌ FirstRanker.com ---

comes to the respondents mind. Both verbal and nonverbal responses are

recorded. Word association frequently used to test potential brand names

and company images among public .interpreting word association tests is

--- Content provided by FirstRanker.com ---


difficult, and the marketing researcher should make sure to avoid subjective

interpretations .when there is considerable agreement in the free-association

--- Content provided by FirstRanker.com ---

process, the researcher assumes that the test has revealed the consumers

inner feelings about the subject

b. Sentence completion test: A projective technique in which respondents are

--- Content provided by​ FirstRanker.com ---


required to complete a number of partial sentences with the first word or

phrase that comes to mind. The sentence completion method is also based

--- Content provided by‌ FirstRanker.com ---

on the principles of free association. For example:

People who smoke are --------

A man who smoke filter cigarette are------

--- Content provided by‍ FirstRanker.com ---


Imported cigarette is most liked by-------


The women in politics are------

--- Content provided by FirstRanker.com ---


When comparing to word association tests the answers given to sentence

completion tests tends to more extensive .the intent of sentence completion

--- Content provided by‌ FirstRanker.com ---

questions are more apparent.



VI- PRODUCT TESTS

--- Content provided by FirstRanker.com ---


Product tests are often completed as part of the 'test' marketing process. Products

are displayed in a mall of shopping center. Potential customers are asked to visit

--- Content provided by FirstRanker.com ---

the store and their purchase behavior is observed. Observers will contemplate

how the product is handled, how the packing is read, how much time the

consumer spends with the product, and so on.

--- Content provided by⁠ FirstRanker.com ---


VII-DIARIES

Diaries are used by a number of specially recruited consumers. They are asked

--- Content provided by FirstRanker.com ---

to complete a diary that lists and records their purchasing behavior of a period of

time (weeks, months, or years). It demands a substantial commitment on the part

of the respondent. However, by collecting a series of diaries with a number of

--- Content provided by‍ FirstRanker.com ---


entries, the researcher has a reasonable picture of purchasing behavior.

VIII-OMNIBUS STUDIES

--- Content provided by‍ FirstRanker.com ---

An omnibus study is where an organization purchases a single or a few

questions on a 'hybrid' interview (either face-to-face or by telephone). The

organization will be one of many that simply want to a straightforward answer

--- Content provided by‍ FirstRanker.com ---


to a simple question. An omnibus survey could include questions from

companies in sectors as diverse as heath care and tobacco. The researches are far

--- Content provided by​ FirstRanker.com ---

cheaper, and commit less time and effort than conducting own research.


IX-CLINICS

--- Content provided by FirstRanker.com ---

The Clinic methodology constitutes a hybrid approach of both qualitative and

quantitative, primarily for testing product or service concepts. A significant

number of respondents are screened and recruited to a central facility (this may

--- Content provided by⁠ FirstRanker.com ---


be a focus group facility or it may be a hotel conference room). Concepts are

presented to the large audience of respondents; videos may be shown; product

--- Content provided by​ FirstRanker.com ---

prototypes may be passed around; client technical people may make parts of the

presentation. Each respondent is provided with a wireless remote answer device

and, during the session, they are asked specific questions and reply in real-time

--- Content provided by​ FirstRanker.com ---


through their wireless devices. Results can, as appropriate, be fed back

instantaneously and are used at the end of the presentation phase to develop a

--- Content provided by‌ FirstRanker.com ---

list of those respondents who have answered in a certain way, and these are

asked to stay for a focus group. Thus the focus group might have people who

liked a new product concept but were only prepared to pay a little for it, or

--- Content provided by‌ FirstRanker.com ---


people who did not like some or all aspects of the product or offer. The result is

a set of quantitative data from the broader audience, and qualitative insight from

--- Content provided by FirstRanker.com ---

the highly focused focus group. The process can be undertaken quickly across

multiple countries and the results made available within a few weeks.

X-SURVEYS

--- Content provided by‍ FirstRanker.com ---


A survey is a research technique in which data are systematically collected

directly from the people being studied by the questionnaire. Surveys are a form

--- Content provided by​ FirstRanker.com ---

of questioning that is more rigid than interviews and that involve larger groups

of people. Surveys will provide a limited amount of information from a large

group of people and are useful when you want to learn what a larger population

--- Content provided by​ FirstRanker.com ---


thinks.

The Steps in a Survey

--- Content provided by FirstRanker.com ---


1. Establish the goals of the survey - What you want to learn

2. Determine your sample - Whom you will interview

--- Content provided by FirstRanker.com ---

3. Choose interviewing methodology - How you will interview

4. Create your questionnaire - What you will ask

5. Pre-test the questionnaire, if practical - Test the questions

--- Content provided by⁠ FirstRanker.com ---


6. Conduct interviews and enter data - Ask the questions

7. Analyze the data - Produce the reports

--- Content provided by​ FirstRanker.com ---

The first step in any survey is deciding what you want to learn. The goals of the

project determine whom you will survey and what you will ask them. If your

goals are unclear, the results will probably be unclear. Some typical goals

--- Content provided by​ FirstRanker.com ---


include learning more about:

The potential market for a new product or service
Ratings of current products or services

--- Content provided by‍ FirstRanker.com ---

Employee attitudes
Customer/patient satisfaction levels
Reader/viewer/listener opinions
Association member opinions
Opinions about political candidates or issues

--- Content provided by‌ FirstRanker.com ---

Corporate images

Selecting the Sample

There are two main components in determining whom you will interview. The

--- Content provided by​ FirstRanker.com ---


first is deciding what kind of people to interview. Researchers often call this

group the target population. If you conduct an employee attitude survey or an

--- Content provided by​ FirstRanker.com ---

association membership survey, the population is obvious. If you are trying to

determine the likely success of a product, the target population may be less

obvious. Correctly determining the target population is critical. If you do not

--- Content provided by‍ FirstRanker.com ---


interview the right kinds of people, you will not successfully meet your goals.

The next thing to decide is how many people you need to interview. Statisticians

--- Content provided by FirstRanker.com ---

know that a small, representative sample will reflect the group from which it is


drawn. The larger the sample, the more precisely it reflects the target group.

--- Content provided by⁠ FirstRanker.com ---

However, the rate of improvement in the precision decreases as your sample size

increases. For example, to increase a sample from 250 to 1,000 only doubles the

precision. You must make a decision about your sample size based on factors

--- Content provided by‌ FirstRanker.com ---


such as: time available, budget and necessary degree of precision.

Avoiding a Biased Sample

--- Content provided by​ FirstRanker.com ---

A biased sample will produce biased results. Totally excluding all bias is almost

impossible; however, if you recognize bias exists you can intuitively discount

some of the answers. The consequences of a source of bias depend on the nature

--- Content provided by FirstRanker.com ---


of the survey. For example, a survey for a product aimed at retirees will not be

as biased by daytime interviews as will a general public opinion survey. A

--- Content provided by FirstRanker.com ---

survey about Internet products can safely ignore people who do not use the

Internet.

Quotas

--- Content provided by⁠ FirstRanker.com ---


A Quota is a sample size for a sub-group. It is sometimes useful to establish

quotas to ensure that your sample accurately reflects relevant sub-groups in your

--- Content provided by‍ FirstRanker.com ---

target population. For example, men and women have somewhat different

opinions in many areas. If you want your survey to accurately reflect the general

population's opinions, you will want to ensure that the percentage of men and

--- Content provided by‌ FirstRanker.com ---


women in your sample reflect their percentages of the general population.

If you are interviewing users of a particular type of product, you probably want

--- Content provided by⁠ FirstRanker.com ---

to ensure that users of the different current brands are represented in proportions

that approximate the current market share. Alternatively, you may want to

ensure that you have enough users of each brand to be able to analyze the users

--- Content provided by FirstRanker.com ---


of each brand as a separate group.

TELEPHONE SURVEYS

--- Content provided by⁠ FirstRanker.com ---


Surveying by telephone is the most popular interviewing method in advanced

countries. Where the time is short and distance is too far the research questions

--- Content provided by​ FirstRanker.com ---

will be asked through telephone .

Advantages

1. People can usually be contacted faster over the telephone than with

--- Content provided by​ FirstRanker.com ---


other methods. If the Interviewers are using CATI (computer-assisted
telephone interviewing), the results can be available minutes after
completing the last interview.

--- Content provided by FirstRanker.com ---

2. You can dial random telephone numbers when you do not have the

actual telephone numbers of potential respondents.

Disadvantages

--- Content provided by​ FirstRanker.com ---


1. Many people are reluctant to answer phone interviews and use their

answering machines to screen calls.

--- Content provided by⁠ FirstRanker.com ---

2. You cannot show your sample products by phone.

MAIL SURVEYS

Mail and telephone surveys are a method of collecting information by sending

--- Content provided by⁠ FirstRanker.com ---


surveys via email or postal mail. Participants return completed forms to the

researcher. Surveys may ask respondents to rate items on a scale .Some surveys

--- Content provided by⁠ FirstRanker.com ---

also allow respondents to write their feelings or attitudes about a particular event

or to elaborate in more detail on an item, or to express suggestions, etc.

Advantages

--- Content provided by‍ FirstRanker.com ---


1. Mail surveys are among the least expensive.
2. This is the only kind of survey you can do if you have the names and

addresses of the target population, but not their telephone numbers.

--- Content provided by‌ FirstRanker.com ---


3. The questionnaire can include pictures - something that is not

possible over the phone.

--- Content provided by FirstRanker.com ---

4. Mail surveys allow the respondent to answer at their leisure, rather

than at the often inconvenient moment they are contacted for a phone
or personal interview. For this reason, they are not considered as
intrusive as other kinds of interviews.

--- Content provided by​ FirstRanker.com ---


Disadvantages

1. Time! Mail surveys take longer than other kinds. You will need to

--- Content provided by‍ FirstRanker.com ---

wait several weeks after mailing out questionnaires before you can be
sure that you have gotten most of the responses.


2. In populations of lower educational and literacy levels, response rates

--- Content provided by⁠ FirstRanker.com ---


to mail surveys are often too small to be useful.

EMAIL SURVEYS

--- Content provided by FirstRanker.com ---

Email surveys are both very economical and very fast. More people have email

than have full Internet access. This makes email a better choice than a Web page

survey for some populations. On the other hand, email surveys are limited to

--- Content provided by FirstRanker.com ---


simple questionnaires, whereas Web page surveys can include complex logic.

Advantages

--- Content provided by​ FirstRanker.com ---

1. Speed. An email questionnaire can gather several thousand

responses within a day or two.

2. There is practically no cost involved once the set up has been

--- Content provided by‍ FirstRanker.com ---


completed.

3. You can attach pictures and sound files.
4. The novelty element of an email survey often stimulates higher

--- Content provided by⁠ FirstRanker.com ---


response levels than ordinary snail mail surveys.

Disadvantages

--- Content provided by‍ FirstRanker.com ---

1. You must possess (or purchase) a list of email addresses.
2. Some people will respond several times or pass questionnaires along

to friends to answer. Many programs have no check to eliminate
people responding multiple times to bias the results. The Survey

--- Content provided by‌ FirstRanker.com ---

System`s Email Module will only accept one reply from each address
sent the questionnaire. It eliminates duplicate and pass along
questionnaires and checks to ensure that respondents have not
ignored instructions (e.g., giving 2 answers to a question requesting
only one).

--- Content provided by⁠ FirstRanker.com ---


3. Many people dislike unsolicited email even more than unsolicited

regular mail. You may want to send email questionnaires only to
people who expect to get email from you.

--- Content provided by​ FirstRanker.com ---


4. You cannot use email surveys to generalize findings to the whole

populations. People who have email are different from those who do
not, even when matched on demographic characteristics, such as age

--- Content provided by‌ FirstRanker.com ---

and gender.

5. Email surveys cannot automatically skip questions or randomize

question or answer choice order or use other automatic techniques

--- Content provided by‍ FirstRanker.com ---

that can enhance surveys the way Web page surveys can.


INTERNET/INTRANET (WEB PAGE) SURVEYS

--- Content provided by FirstRanker.com ---

Web surveys are rapidly gaining popularity. They have major speed, cost, and

flexibility advantages, but also significant sampling limitations. These

limitations make software selection especially important and restrict the groups

--- Content provided by⁠ FirstRanker.com ---


you can study using this technique.

Advantages

--- Content provided by FirstRanker.com ---

1. Web page surveys are extremely fast. A questionnaire posted on a

popular Web site can gather several thousand responses within a few
hours. Many people who will respond to an email invitation to take a
Web survey will do so the first day, and most will do so within a few

--- Content provided by⁠ FirstRanker.com ---

days.

2. There is practically no cost involved once the set up has been

completed. Large samples do not cost more than smaller ones

--- Content provided by‌ FirstRanker.com ---

(except for any cost to acquire the sample).

3. You can show pictures. Some Web survey software can also show

video and play sound.

--- Content provided by​ FirstRanker.com ---


4. Web page questionnaires can use complex question skipping logic,

randomizations and other features not possible with paper
questionnaires or most email surveys. These features can assure

--- Content provided by‍ FirstRanker.com ---

better data.

5. Web page questionnaires can use colors, fonts and other formatting

options not possible in most email surveys.

--- Content provided by‍ FirstRanker.com ---


6. A significant number of people will give more honest answers to

questions about sensitive topics, such as drug use or sex, when giving
their answers to a computer, instead of to a person or on paper.

--- Content provided by‌ FirstRanker.com ---


7. On average, people give longer answers to open-ended questions on

Web page questionnaires than they do on other kinds of self-
administered surveys.

--- Content provided by⁠ FirstRanker.com ---


Disadvantages

1. Current use of the Internet is far from universal. Internet surveys do

--- Content provided by‌ FirstRanker.com ---

not reflect the population as a whole. This is true even if a sample of
Internet users is selected to match the general population in terms of
age, gender and other demographics.

2. People can easily quit in the middle of a questionnaire. They are not

--- Content provided by‍ FirstRanker.com ---


as likely to complete a long questionnaire on the Web, as they would
be if talking with a good interviewer.


--- Content provided by FirstRanker.com ---

3. If your survey pops up on a web page, you often have no control over

who replies - anyone from Antarctica to Zanzibar, cruising that web
page may answer.

--- Content provided by FirstRanker.com ---

4. Depending on your software, there is often no control over people

responding multiple times to bias the results.

Things to consider when conducting surveys:

--- Content provided by⁠ FirstRanker.com ---


Who are you planning on surveying? Decide what group you are going to

focus on surveying based on who you have access to and what your research is

--- Content provided by​ FirstRanker.com ---

focused on.

How many people are you going to survey? You want to choose a target

number of surveys to conduct. You don't want too few surveys because you

--- Content provided by FirstRanker.com ---


won't have enough answers to support any generalizations or findings you may

make. At the same time, you do not want too many surveys because you will be

--- Content provided by⁠ FirstRanker.com ---

overwhelmed with analyzing your data.

How are you going to survey people? You can choose to conduct your survey

in person (i.e. walk up to people and ask them questions); on paper (i.e. hand out

--- Content provided by‌ FirstRanker.com ---


surveys and ask people to return them); or even via the Internet. The survey

method should be chosen based on the length of your survey and types of

--- Content provided by‍ FirstRanker.com ---

questions.

How long is your survey going to be? The answer to this question depends on

what information you are attempting to discover and how much you want to find

--- Content provided by‌ FirstRanker.com ---


out. Longer surveys sometimes involve the same question asked in multiple

ways to see if people are consistent in their answering strategies. For your first

--- Content provided by‍ FirstRanker.com ---

survey, however, it is better to keep things simple. Short questions are usually

more effective than longer ones.

What type of questions are you going to ask? Do you want open-ended

--- Content provided by‍ FirstRanker.com ---


questions or closed questions? Open-ended questions are questions that allow

the participant any type of response. An example of an open-ended question is:

--- Content provided by‌ FirstRanker.com ---

How are you feeling today? A closed question is one with a set of possible

responses or yes/no responses. An example is: Did you feel that the new campus

regulation about parking is fair? While closed questions are much easier to

--- Content provided by⁠ FirstRanker.com ---


analyze they do not provide the rich responses you may get with open-ended

questions. Ultimately, what type of question you ask depends on what you want

--- Content provided by​ FirstRanker.com ---

to discover.


SURVEY CHARACTERISTICS

--- Content provided by​ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

Survey

Mail survey

Telephone

--- Content provided by⁠ FirstRanker.com ---


Personal

characteristics

--- Content provided by FirstRanker.com ---

survey

interview survey


--- Content provided by‌ FirstRanker.com ---






--- Content provided by FirstRanker.com ---



Lowest

Moderate

--- Content provided by‌ FirstRanker.com ---


High



--- Content provided by‌ FirstRanker.com ---





Cost

--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---



Wide

Wide

--- Content provided by​ FirstRanker.com ---


Moderate



--- Content provided by‍ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---


Geographic



--- Content provided by​ FirstRanker.com ---





distribution

--- Content provided by FirstRanker.com ---


Low

Moderate

--- Content provided by​ FirstRanker.com ---

High




--- Content provided by⁠ FirstRanker.com ---






--- Content provided by FirstRanker.com ---

Flexibility and




--- Content provided by​ FirstRanker.com ---




questioning

--- Content provided by⁠ FirstRanker.com ---

No

Moderate

High

--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by FirstRanker.com ---



Interviewer bias

Slowest

--- Content provided by FirstRanker.com ---


Fastest

Moderate

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---


Speed and data

Lowest

--- Content provided by‌ FirstRanker.com ---

Moderate

Highest

collection

--- Content provided by‍ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---

Control and data

Poor

Moderate

--- Content provided by FirstRanker.com ---


Highest

collection

--- Content provided by‌ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---


Response rates



--- Content provided by‍ FirstRanker.com ---

XI-CASE STUDY



Case study is a vaery popular method of qualitative research.It involves a

--- Content provided by​ FirstRanker.com ---


careful and complete observation rather than using large samples and following

a rigid protocol to examine a limited number of variables, case study methods

--- Content provided by​ FirstRanker.com ---

involve an in-depth, longitudinal examination of a single instance or event: a

case. They provide a systematic way of looking at events, collecting data,

analyzing information, and reporting the results. As a result the researcher may

--- Content provided by FirstRanker.com ---


gain a sharpened understanding of why the instance happened as it did, and what

might become important to look at more extensively in future research. Case

--- Content provided by FirstRanker.com ---

studies lend themselves especially to generating (rather than testing) hypothesis

The design involves the intense investigation of situations which are relevant to

the problem situation.The concept is to select several target cases where an

--- Content provided by​ FirstRanker.com ---


intensive analysis will help to

Know the environment

--- Content provided by⁠ FirstRanker.com ---

Identify relevant variables

Indicate nature of relationship among the variable

Identify the naure of roblems and opportunies in the orginal case.

--- Content provided by​ FirstRanker.com ---


The case history method is especially useful in situations in which a complicated

series of variables interact to produce the problem or opportunity .

--- Content provided by FirstRanker.com ---

PRIMARY vs. SECONDARY SOURCE OF DATA

Primary sources are the raw material of the research process, they represent the

records of research or events as first described. Secondary sources are based on

--- Content provided by‌ FirstRanker.com ---


primary sources. These sources analyze, describe, and synthesize the primary or

original source. Usage of primary source and secondary source should be

--- Content provided by‍ FirstRanker.com ---

complementary. Savvy entrepreneurs will do secondary research first and then

conduct primary research. For example, the owner of a video-rental shop would

want to know all about a neighborhood before opening a new store there. Using

--- Content provided by‌ FirstRanker.com ---


information gleaned from secondary sources, the owner can find all kinds of

demographic data, including detailed income data and spending patterns. They

--- Content provided by​ FirstRanker.com ---

can then send out a questionnaire to a sampling of households to find out what

kinds of movies people like to rent. That primary-research technique will help

when it comes time to stock the store with the latest Hollywood releases.

--- Content provided by‍ FirstRanker.com ---


Secondary research lays the groundwork and primary research helps fill in the

gaps. By using both types of market research, business owners get a well-

--- Content provided by‌ FirstRanker.com ---

rounded view of their market and have the information they need to make

important business decisions. The selection of methods depends upon various

factors like

--- Content provided by⁠ FirstRanker.com ---


1. Scope of the study.

2. Objectives of the study.

--- Content provided by⁠ FirstRanker.com ---

3. Time availability for the study.

4. Degree of accuracy needed.

5. Study environment, respondents.

--- Content provided by‍ FirstRanker.com ---


6. Budget estimated.

IV.C. FIELD OPERATIONS

--- Content provided by‍ FirstRanker.com ---

Learning objectives

After reading this part, you may be able familiar with the following topics

Objectives of field operations in marketing research.

--- Content provided by⁠ FirstRanker.com ---

Functions involved in field operation.



The actual data collection process is rarely done by the person who designs the

--- Content provided by‍ FirstRanker.com ---


research. An irony of marketing research is that highly educated and trained

individuals will design the research, but the people who gather the data typically

--- Content provided by⁠ FirstRanker.com ---

have little research training and experience. Field operation is that phase of the

project during which researchers make contact with the respondents,

administrator the data collection instruments, record the data, and return the data

--- Content provided by FirstRanker.com ---


to a central location for processing. The wisdom behind the research design and

skill involved in developing the data collection instrument will be wasted in the

--- Content provided by⁠ FirstRanker.com ---


field operation is poorly administrated. The planning of the field operation is

highly influenced by data collection method employed.

--- Content provided by‍ FirstRanker.com ---

Marketing managers preparing for the fieldwork operation should concentrate

on the following areas.

1. Briefing sessions for field workers.

--- Content provided by‌ FirstRanker.com ---

2. Supervision of the fieldwork
3. Verification

Briefing for field workers:

--- Content provided by⁠ FirstRanker.com ---

A proper research design will eliminate numerous sources of error, but careful

execution of the fieldwork is necessary to produce results without substantial

error. For the best execution the fieldworkers must be properly trained. Whether

--- Content provided by​ FirstRanker.com ---


the fieldworkers/interviewers have just completed their training in basics or are

already experienced, there is a need to inform them about the current research.

--- Content provided by FirstRanker.com ---

Both experienced and inexperienced fieldworkers must be briefed on the

background of the project, study method sampling technique. Instruction s for

handling certain key situations are always important. To train the fieldworkers

--- Content provided by FirstRanker.com ---


about the questionnaire, a field supervisor can elaborate the questions and its

purpose. The general cautions to be taken by the fieldworkers can also be

--- Content provided by​ FirstRanker.com ---

outlined

The briefing session will also cover the sampling procedure. A number of

research projects allow the interviewer to be at least partially responsible for

--- Content provided by⁠ FirstRanker.com ---


selecting sample. When this is the case, the potential for selection bias exists.

For example in quota sample the field worker may select a wrong sample due to

--- Content provided by⁠ FirstRanker.com ---

poor awareness about the importance of the quota representation. In addition to

technical procedure few general guidelines can also be given to these

fieldworkers, like the ethics in conducting field work.

--- Content provided by FirstRanker.com ---


Supervision of Fieldwork:

Irrespective of the training given to the field workers, they may commit few

--- Content provided by FirstRanker.com ---

errors in execution. Direct supervision of personal interviewers, telephone

interviewers and other fieldworkers is necessary to ensure that the technique

communicated in the training sessions are implemented in the field. The

--- Content provided by FirstRanker.com ---


supervision of fieldworkers, like other forms of supervision, refers to controlling

the efforts of workers. Field supervision of fieldworkers requires checking to see

--- Content provided by‍ FirstRanker.com ---

that field procedures are being properly followed. The supervisor checks field

operations to ensure that the interviewing schedule is being met. In addition to

quality control, continual training may be provided. For example, a telephone

--- Content provided by‌ FirstRanker.com ---


supervisor may notice that interviewers are allowing the phone to ring

continuously before considering the call a no answer. The supervisor can

--- Content provided by​ FirstRanker.com ---

instruct interviewers that if a telephone is allowed to ring too long and then

answered, the respondent may be annoyed

Verification: It is the quality control procedures in fieldwork to ensure that

--- Content provided by FirstRanker.com ---


interviewers are following the field plan. At the field the most important job of

the supervisor is to verify that the interviews are being conducted according to

--- Content provided by FirstRanker.com ---

the schedule and the plan. An interviewer might be tempted to skip the process

for various reasons. Careful recording of the number of completed interviews

will help ensure that the sampling procedure is being properly conducted. It is

--- Content provided by FirstRanker.com ---


the supervisors function to motivate interviewers to carefully follow the plan.

Where ever the deficiency is found the supervisor should take remedial actions

--- Content provided by‌ FirstRanker.com ---

to solve the complication.

IV.D. ERRORS AND DIFFICULTIES

Learning objectives

--- Content provided by⁠ FirstRanker.com ---


After reading this part, you may be able familiar with the following topics

Sources error in marketing research
Impact of errors on research

--- Content provided by‌ FirstRanker.com ---

Types of errors


i) ERRORS :

--- Content provided by‌ FirstRanker.com ---

Since the usability of any market research depends upon the accuracy of the

results, error control plays a critical role in the research process. Every step in

the marketing research progression can produce serious errors. The control of

--- Content provided by‌ FirstRanker.com ---


these errors is of critical concern in marketing research. Avoiding many of the

simpler marketing research errors takes only common sense, but avoiding many

--- Content provided by‍ FirstRanker.com ---

of the more complex mistakes requires a much deeper level of awareness. The

common marketing research errors are highlighted below.

Types of errors

--- Content provided by FirstRanker.com ---


Sampling errors

Non sampling errors

--- Content provided by⁠ FirstRanker.com ---

Sampling errors
Most marketing research studies utilize samples of people, product or stores.

Based upon these sample results, the researcher and the manager make

--- Content provided by FirstRanker.com ---

conclusion of the whole population from which the sample was selected. For

example the attitudes of all Maruti car owners could be inferred from a sample

of a 1000 owners because the

--- Content provided by FirstRanker.com ---




ERRORS

--- Content provided by FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---



NON

SAMPLING

--- Content provided by‌ FirstRanker.com ---




ERRORS

--- Content provided by‍ FirstRanker.com ---



SAMPLIN

G

--- Content provided by‌ FirstRanker.com ---


ERRORS



--- Content provided by⁠ FirstRanker.com ---



SAMPLING

NON RESSPONSE

--- Content provided by​ FirstRanker.com ---


DATA ERRORS

FRAME ERRORS

--- Content provided by⁠ FirstRanker.com ---

ERRORS




--- Content provided by⁠ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

NONCOVE

OVERCOVE

MEASEUREMENT

--- Content provided by⁠ FirstRanker.com ---


PROCES

ERRORS

--- Content provided by‍ FirstRanker.com ---

INTERVIE



RAGE

--- Content provided by⁠ FirstRanker.com ---


RAGE

SING

--- Content provided by FirstRanker.com ---

WER

ERRORS

ERRORS

--- Content provided by FirstRanker.com ---


ERRORS

ERRORS

--- Content provided by​ FirstRanker.com ---






--- Content provided by FirstRanker.com ---


sample is used to estimate the population. The difference between the sample

value and the corresponding population value is called as sampling error .

--- Content provided by⁠ FirstRanker.com ---

Non sampling errors
Non sampling errors are all the errors that may occur in the marketing research

process except the sampling error. This concept simply includes all the aspects

--- Content provided by⁠ FirstRanker.com ---

of the research process where mistakes and deliberate deceptions can occur..

Unfortunately these mistakes and deceptions occur with great frequency in the

marketing research process. An important point to note is that sampling error is

--- Content provided by⁠ FirstRanker.com ---


measurable while it is not easy to measure as non-sampling error.

Hence, the researcher should take care of the following points to deal with non-

--- Content provided by⁠ FirstRanker.com ---

sampling error.

What kind of non- sampling errors may occur.

What effects these errors may have on our results, and

--- Content provided by⁠ FirstRanker.com ---


What steps we can take to reduce these errors.

The effect of non sampling errors:

--- Content provided by​ FirstRanker.com ---

Sampling error has two properties that make it useful to the researcher.

measurable


--- Content provided by​ FirstRanker.com ---

relevance with sample size

Unfortunately non sampling errors are not easily measurable and they do not

decrease with sample size. Infact in all likelihood non sampling errors increase

--- Content provided by‍ FirstRanker.com ---


as sample size increases. What non sampling errors do is put a bias in results of

unknown direction and magnitude

--- Content provided by‍ FirstRanker.com ---

TYPES OF NON SAMPLING ERRORS:

Defective problem definition:

Problem of the study should be clearly stated so that they can be linked directly

--- Content provided by‍ FirstRanker.com ---


to the research results. Research objectives should always be clear so that

research results can be presented in relation to specific objectives. A product

--- Content provided by FirstRanker.com ---

manager requests a study to test a media mix. If the true problem is pricing

strategy then any research that is conducted no matter how technically correct

will not be helpful to the manager.

--- Content provided by FirstRanker.com ---


Defective population definition:

The study population must be defined to fit the study objectives. A universe

--- Content provided by​ FirstRanker.com ---

which is relevant to the problem being studied, and a sample which adequately

represents that universe, are vital requirements of high quality research.

Consider the case of the manager of one of the restaurants in a major

--- Content provided by⁠ FirstRanker.com ---


metropolitan airport would like to know what sort of image the restaurant has

among those who have some likelihood of eating in the airport. The population

--- Content provided by‌ FirstRanker.com ---

is defined as people over 18 years old, getting off planes in the third week of

October. If the sample is selected from this population one might get misleading

results. It does not include significant numbers of potential customers that is

--- Content provided by​ FirstRanker.com ---


people who are just taking off. Also the sample included people who has no

chance of eating in the restaurants. That is people who change planes without

--- Content provided by​ FirstRanker.com ---

going into the main terminal where the restaurants are located. Conclusions from

this study are questionable.

Frame non representative of the population:

--- Content provided by⁠ FirstRanker.com ---


There are many acceptable methods of sampling, each with advantages and

disadvantages in specific situations. The following guidelines are not meant to

--- Content provided by⁠ FirstRanker.com ---

specify how sampling must be designed or managed, but rather are aimed at

insuring that sample design and management are disclosed in sufficient detail to

allow clear judgments of a sample's adequacy for the stated research purpose.

--- Content provided by‌ FirstRanker.com ---


The sampling frame must match the defined population. Consider the case of

the investment company that uses the telephone book (the frame)to select a

--- Content provided by FirstRanker.com ---

sample of potential stock buyers this frame would not cover the defined

population well as a

significant number of high income people have unlisted phone numbers. These

--- Content provided by‌ FirstRanker.com ---


high income people are the prime potential stock buyers. Again conclusions are

suspects.

--- Content provided by⁠ FirstRanker.com ---

Non responsive errors:

Errors occur because people in selected sample either refuse to be a part of the

sample or they are not at home during the sample periods. a sample is a

--- Content provided by‍ FirstRanker.com ---


representative sample as selected. Some of the selected elements do not form

part of the realized sample, it is not a truly representative sample. The resulting

--- Content provided by‌ FirstRanker.com ---

error is called non?response error. As an example of this problem consider the

case of a resort developer who attempts to interview people during the day. The

study yields some refusals and a lot of not at homes. One must wonder

--- Content provided by‌ FirstRanker.com ---


whether the refusals as a group hold different attitudes of the development from

those who respond.

--- Content provided by⁠ FirstRanker.com ---

Questionnaire structure error:

The error made when the structure and layout of the survey instrument leads to

inaccurate responses. For example asking probing questions regarding

--- Content provided by‌ FirstRanker.com ---


viewpoints on potentially negative experiences before asking an overall


satisfaction question, where overall satisfaction would be incorrectly affected by

--- Content provided by​ FirstRanker.com ---


the recent recall of potentially bad experiences.

Measurement error :

--- Content provided by FirstRanker.com ---

This is caused when information gathered is different from the information

sought. For example, respondents are asked to indicate whether they own a car

or not. Some of them may respond in the positive just to boost their image

--- Content provided by FirstRanker.com ---


before an interviewer, even though they may not be owning a car. Such

responses will result in measurement error.

--- Content provided by⁠ FirstRanker.com ---

Data analysis error:

The error that occurs when analysis is incorrectly executed. Simple

mathematical errors are common, which is why data analysis should be checked

--- Content provided by⁠ FirstRanker.com ---


over by more than one qualified person for quality. A more significant data

analysis error is when simple frequency reporting (straight number percentage

--- Content provided by FirstRanker.com ---

reporting) is executed when far greater information can be mined from the

results (often inexpensively) through additional analysis such as cross-tabulation

analysis, multiple regression (driver analysis), cluster analysis, factor analysis,

--- Content provided by‌ FirstRanker.com ---


perceptual mapping (multidimensional scaling), structural equation modeling

tests, etc.

--- Content provided by⁠ FirstRanker.com ---

Reporting error:

The best approach and program design combined with the best analysis is only

as good as the researcher`s capability to synthesize and report on the results. The

--- Content provided by⁠ FirstRanker.com ---


most common reporting error by far is the improper representation of the

significant findings in a format conducive to creating management

--- Content provided by​ FirstRanker.com ---

understanding and buy-in of survey results. It could be something as simple as

poor language syntax to as complex as choosing the wrong results to report or

not choosing the best way to graphically represent the results. More common in

--- Content provided by‌ FirstRanker.com ---


the current environment is not selecting the best delivery vehicle. For example, a


quality online reporting system is much preferred when distributing results

--- Content provided by⁠ FirstRanker.com ---


across a company that is geographically spread out.

Common sources of error in field work:

--- Content provided by FirstRanker.com ---

Five common sources of error in field work are identified in the following

discussion:

1. errors in selecting respondents

--- Content provided by​ FirstRanker.com ---


2. non-response errors (i.e. failure to get data from selected respondents)

3. errors created by the method of seeking data

--- Content provided by​ FirstRanker.com ---

4. errors resulting from interviewer`s misinterpreting or misrecording

answers; and

5. interviewer cheating

--- Content provided by​ FirstRanker.com ---




Respondent selection errors:

--- Content provided by​ FirstRanker.com ---

Telephone errors:

In telephone surveys the interviewer is typically given a list of numbers to call,

or numbers are dialed on the basis of random-digit dialing. If the interviewer in

--- Content provided by‍ FirstRanker.com ---


the former case is also given the name of the individual at each number to whom

she is to speak, there is no problem, as the interviewer simply asks for that

--- Content provided by‍ FirstRanker.com ---

individual by name. Unfortunately, names are seldom available, and the

interviewer must select the individual to be interviewed at the number called-

usually a household.

--- Content provided by‌ FirstRanker.com ---


Mail intercept interviews:

In the case of shopping center interviews, respondents are often selected by

--- Content provided by​ FirstRanker.com ---

convenience. It cannot be said that errors are made in respondent selection when

this is the case, but the procedure is often biased because interviewers are likely

to select those individuals who look friendly and appear easy to interview. To

--- Content provided by​ FirstRanker.com ---


introduce more objectivity into the process, specific times and locations within

the shopping center can be selected randomly, and it can be specified that the

--- Content provided by‌ FirstRanker.com ---

first person passing a given point after each interview or attempted interview

will be sought as the next respondent.

Door-door surveys:

--- Content provided by‍ FirstRanker.com ---


When quota samples are used in door-door surveys, interviewers select the

individuals to be interviewed subject only to quotas for various population

--- Content provided by⁠ FirstRanker.com ---

groups such as sex, age and income. This interviewer control of the selection of

the respondents is unlikely to result in the equivalent of a random sample.

Interviewers tend to follow the paths of least resistance and greatest

--- Content provided by‌ FirstRanker.com ---


convenience.

Not -at -homes:

--- Content provided by​ FirstRanker.com ---

The percentage of not-at-homes varies by city size, day of the week, time of day,

season of the year, age and the sex of the respondent, as well as with the

provisions made to control not-at-homes in the individual studies. It is, however,

--- Content provided by​ FirstRanker.com ---


almost always surprisingly large. Failure to obtain data from not-at-homes may

bias survey results because population groups vary in the probability of being at

--- Content provided by FirstRanker.com ---

home.

Refusals:

Refusal rates vary from project to project and may range up to 20%. Since

--- Content provided by‍ FirstRanker.com ---


refusals are often the result of personality and mood, it can be argued that they

will occur randomly and will not bias results. Moreover, refusals are a matter of

--- Content provided by​ FirstRanker.com ---

degree and of circumstances such as convenience at time of call. Repeated

efforts to obtain compliance can reduce the refusal rate, but only to a degree. In

addition to general refusals, refusals may occur on specific questions,

--- Content provided by‍ FirstRanker.com ---


particularly those relating to income and other personal questions.

ii) MINIMIZING OF ERRORS:

--- Content provided by‍ FirstRanker.com ---

In research it is not possible to eliminate all the errors .However, to the extent

that can be minimized. The following precautions can be followed to reduce the

errors :

--- Content provided by​ FirstRanker.com ---


Selection of suitable study method

Selection of appropriate instrument

--- Content provided by⁠ FirstRanker.com ---

Adequate sample size

Using of trained and experiences researchers

Planned data processing

--- Content provided by‍ FirstRanker.com ---


iii) DIFFICULTIES IN DATA COLLECTION

Marketing research basically a problem solving tool. Starting from the definition

--- Content provided by​ FirstRanker.com ---

of the problem till the end of the presentation of the report researchers are

facing numerous problems. The major problems faced by the researchers are

mentioned below:

--- Content provided by‍ FirstRanker.com ---




1. Volatile changes in the business environment make marketing research

--- Content provided by​ FirstRanker.com ---

more complicated. Continuous changes in market make the results of the
study unsuitable.

2. Lack of scientific training and application in marketing research

--- Content provided by​ FirstRanker.com ---

methodology is a major problem in our country .

3. The Research and Development Department has become a common

feature in many organizations. But decisions makers do not appear to be

--- Content provided by FirstRanker.com ---

very eager on implement the findings of the study.

4. Many of the organizations are not reach conscious and feel that

investment in research is wastage of resources and does not encourage

--- Content provided by‌ FirstRanker.com ---

research.

5. Many people largely depend on customs, traditions and routine practices

in their decision making, as they feel research does not have any useful

--- Content provided by⁠ FirstRanker.com ---

purpose to serve in the management of their business.

6. The secrecy of business information is sacrosanct to business

organizations. Most of the business organizations in our country do not

--- Content provided by‌ FirstRanker.com ---

part with information to researchers.

7. There is insufficient support between the business organizations and

research institutions, which essential for the development of good and

--- Content provided by‍ FirstRanker.com ---

meaningful research.

8. In India companies are not in a position to allocate huge funds for the

research.

--- Content provided by​ FirstRanker.com ---



9. Lack of availability secondary data makes marketing research as

baseless start and time consuming one.

--- Content provided by FirstRanker.com ---


10. Poor awareness among the consumers about research makes the study

more burning.

--- Content provided by‍ FirstRanker.com ---

11. Researchers in India are not familiar with the new research instruments

available for conducting market research,

12. poor library facilities at any places, because of which researchers have to

--- Content provided by FirstRanker.com ---


spend much of time and energy in tracing out relevant material and
information.

13. there is a difficulty of timely availability of upto date data from

--- Content provided by‍ FirstRanker.com ---


published sources

14. Lack of code of conduct among the researchers brings bad image on

--- Content provided by FirstRanker.com ---

research. There is a need for developing code of conduct for researchers
to educate them about ethical aspects of research.



--- Content provided by‍ FirstRanker.com ---



IV.E. DATA PROCESSING

Learning objectives

--- Content provided by‌ FirstRanker.com ---


In this chapter you will learn about

Objective of data processing
Functions involved in data processing

--- Content provided by​ FirstRanker.com ---

Process of editing and coding.

Once the collection of data is over, the next step is to organize data so that

meaningful conclusions may be drawn. The information content of the

--- Content provided by FirstRanker.com ---


observations has to be reduced to a relatively few concepts and aggregates. The

data collected from the field has to be processed as laid down in the research

--- Content provided by⁠ FirstRanker.com ---

plan. This is possible only through systematic processing of data. Data

processing involves editing, coding, classification and tabulation of the data

collected so that they are amenable to analysis. This is an intermediary stage

--- Content provided by‌ FirstRanker.com ---


between the collection of data and their analysis and interpretation.

i) EDITING OF DATA

--- Content provided by‍ FirstRanker.com ---


Editing is the first stage in data processing. Editing may be broadly defined to be

a procedure, which uses available information and assumptions to substitute

--- Content provided by‍ FirstRanker.com ---

inconsistent values in a data set. In other words, editing is the process of

examining the data collected through various methods to detect errors and

omissions and correct them for further analysis. While editing, care has to be

--- Content provided by FirstRanker.com ---


taken to see that the data are as accurate and complete as possible, units of

observations and number of decimal places are the same for the same variable.

--- Content provided by⁠ FirstRanker.com ---

The following practical guidelines may be handy while editing the data:

1. The editor should have a copy of the instructions given to the

interviewers.

--- Content provided by⁠ FirstRanker.com ---


2. The editor should not destroy or erase the original entry. Original entry

should be crossed out in such a manner that they are still legible.

--- Content provided by‌ FirstRanker.com ---

3. All answers, which are modified or filled in afresh by the editor, have to

be indicated.

4. All completed schedules should have the signature of the editor and the

--- Content provided by‍ FirstRanker.com ---


date.

For checking the quality of data collected, it is advisable to take a small sample

--- Content provided by‍ FirstRanker.com ---

of the questionnaire and examine them thoroughly. This helps in understanding

the following types of problems:

1. Whether all the questions are answered,

--- Content provided by⁠ FirstRanker.com ---


2. Whether the answers are properly recorded,

3. Whether there is any bias,

--- Content provided by​ FirstRanker.com ---

4. Whether there is any interviewer dishonesty,

5. Whether there are inconsistencies.

At times, it may be worthwhile to group the same set of questionnaires

--- Content provided by‍ FirstRanker.com ---


according to the investigators (whether any particular investigator has specific

problems) or according to geographical regions (whether any particular region

--- Content provided by​ FirstRanker.com ---


has specific problems) or according to the sex or background of the

investigators, and corrective actions may be taken if any problem is observed.

--- Content provided by⁠ FirstRanker.com ---

Mechanics of editing:
For editing purpose the researcher must draw a proper mechanism which will

simplify the process as well as reduces the duplication work. Data frequently are

--- Content provided by FirstRanker.com ---

written in with a colored pen or pencil .When space on the questionnaire

permits, the original data usually are left in to permit a subsequent edit and to

identify the originals concepts. Before tabulation of data it may be good to

--- Content provided by FirstRanker.com ---


prepare an operation manual to decide the process for identifying inconsistencies

and errors and also the methods to edit and correct them.

--- Content provided by⁠ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---

Types of editing
1.Field editing: Preliminary editing by a field supervisor on the interview to

catch technical omissions, check legibility of hand writing and clarify responses

--- Content provided by​ FirstRanker.com ---

that are logically inconsistent

2.In-house editing: A rigorous editing job performed by a centralized office

staff. The researcher normally has centralized office staff to perform editing and

--- Content provided by⁠ FirstRanker.com ---


coding. The researcher must setup a centralized office with all facilities for

editing and coding purposes by which coordination can be accomplished

--- Content provided by​ FirstRanker.com ---




ii ) CODING OF DATA

--- Content provided by FirstRanker.com ---

Coding refers to the process by which data are categorized into groups and

numerals or other symbols or both are assigned to each item depending on the

class it falls in. Hence, coding involves:

--- Content provided by​ FirstRanker.com ---


Deciding the categories to be used, and

Assigning individual codes to them.

--- Content provided by FirstRanker.com ---

For example, for the open-ended question Do you enjoy milkshakes, if so,

how much would you say you enjoy milkshakes. The researcher in the coding

process will then have to observe different answers and give them a numeric

--- Content provided by​ FirstRanker.com ---


value. For example, If we use a five-point scale with 1 being low (don`t

enjoy`) and 5 being high (favorite treat`), and the response is I like

--- Content provided by⁠ FirstRanker.com ---

milkshakes ? the researcher would code the response as a 3, if the response

was I absolutely love milkshakes! the researcher would code the response as a

5.

--- Content provided by‌ FirstRanker.com ---


In general, coding reduces the huge amount of information collected into a form

that is amenable to analysis. A careful study of the answers is the starting point

--- Content provided by‍ FirstRanker.com ---

of coding. Next, a coding frame is to be developed by listing the answers and by

assigning the codes to them. A coding manual is to be prepared with the details

of variable names, codes and instructions. Normally, the coding manual should

--- Content provided by⁠ FirstRanker.com ---


be prepared before collection of data, but for open-ended and partially coded

questions. These two categories are to be taken care of after the data collection.

--- Content provided by‍ FirstRanker.com ---

The following are the broad general rules for coding:

1. Each respondent should be given a code number (an identification

number).

--- Content provided by⁠ FirstRanker.com ---


2. Each qualitative question should have codes. Quantitative variables

mayor may not be coded depending on the purpose. Monthly income
should not be coded if one of the objectives is to compute average

--- Content provided by‍ FirstRanker.com ---



monthly income- But if it is used as a classificatory variable it may
be coded to indicate poor, middle or upper Income group.

--- Content provided by‍ FirstRanker.com ---

3. All responses including "don't know", "no opinion" "no response"

etc., are to be coded.

4. Sometimes it is not possible to anticipate all the responses and some

--- Content provided by​ FirstRanker.com ---


questions are not coded before collection of data. Responses of all
the questions are to be studied carefully and codes are to be decided
by examining the essence of the answers. In partially coded
questions, usually there is an option " Any other (specify)".

--- Content provided by FirstRanker.com ---

Depending on the purpose, responses to this question may be
examined and additional codes may be assigned.



--- Content provided by‍ FirstRanker.com ---

Production coding:

The actual process of transferring the data from the questionnaire or data

collection form after the data have been collected is called production coding.

--- Content provided by⁠ FirstRanker.com ---


Based on the nature of the data collection tool, codes may be written directly on

the instrument or special coding sheet. Coding should be done in a central

--- Content provided by‍ FirstRanker.com ---

location so that a supervisor can help to solve interpretation problems.

Computerized coding:

Studies having large sample size uses a computer system for coding as well as

--- Content provided by⁠ FirstRanker.com ---


data processing. The process of transferring data from a research project, such as

answers to survey questionnaire, to computer is referred to as data entry.

--- Content provided by‌ FirstRanker.com ---

Several alternative means of entering data in to the computer are also available.

A

researcher using computer?assisted telephone interviewing or with on-line

--- Content provided by FirstRanker.com ---


direct data entry equipment automatically stores and tabulates responses as they

are collected. Optical Scanning Systems may also be used to directly read

--- Content provided by‌ FirstRanker.com ---

material from marked sheets.



CHAPTER SUMMARY

--- Content provided by​ FirstRanker.com ---



In marketing research the process of data collections plays a vital role .In this

chapter you have studied about data instruments, features of different data

--- Content provided by​ FirstRanker.com ---


collection methods and data processing. Based on the study selected the

researcher either can go for secondary source or primary data collection and for

--- Content provided by FirstRanker.com ---

both .The process of editing and coding shapes the data to get the maximum

results.

KEY WORDS

--- Content provided by FirstRanker.com ---


Data: Quantitative or/ and qualitative information, collected for study and

analysis.

--- Content provided by⁠ FirstRanker.com ---

Case study: the exploratory research technique that intensively investigates one

or a few situations similar to the problem situation.

Coding: The process of identifying and assigning score or other character

--- Content provided by​ FirstRanker.com ---


symbol to previously edited data.

Editing: the process of checking completeness, consistency, and legibility of

--- Content provided by‍ FirstRanker.com ---

data and making the data ready for coding and transfer to storage.

Interview: A method of collecting primary data by meeting the informants and

asking the questions.

--- Content provided by‍ FirstRanker.com ---


Observation: The process of observing individuals in controlled situations.

Questionnaire: is a device for collection of primary data containing a list of

--- Content provided by‍ FirstRanker.com ---

questions pertaining to enquiry, sent to the informants, and the informant

himself writes the answers.

Primary Data: Data that is collected originally for the first time.

--- Content provided by⁠ FirstRanker.com ---




Secondary Data: Data which were collected and processed by someone else but

--- Content provided by‌ FirstRanker.com ---

are being used in the present study.

Published Sources: Sources which consist of published statistical information.


--- Content provided by‍ FirstRanker.com ---

Schedule: is a device for collection of primary data containing a list of

questions to be filled in by the enumerators who are specially appointed for that

purpose.

--- Content provided by‍ FirstRanker.com ---


Survey : a method of primary data collection in which information is gathered

by communicating with a representative sample of people.

--- Content provided by‍ FirstRanker.com ---



Questions for practice


--- Content provided by​ FirstRanker.com ---


1. What are the qualities of a good research instrument?
2. Enumerate the different methods of data collection.
3. Explain the merits and limitations of using secondary data.
4. What precautions would you take while using the data from secondary

--- Content provided by‌ FirstRanker.com ---


sources?

5. Explain the various sources of primary data.
6. What is observation? Explain the role of observer in the process of

--- Content provided by‍ FirstRanker.com ---


observation.

7. Examine the merits and limitations of the observation method.
8. Explain different methods of conducting interviews.

--- Content provided by‌ FirstRanker.com ---

9. How does the case study method differ from the survey method? analyse

the merits and limitations of case study method in marketing research

10. What are the guidelines in the construction of questionnaire? Explain.

--- Content provided by‍ FirstRanker.com ---

11. What is field operations? Explain the cautions to be taken by the

researcher in field operations.

12. What is data processing? Explain the various functions of data

--- Content provided by FirstRanker.com ---


processing.

13. Explain the importance of data editing in marketing research.
14. Explain the main sources of error in field operations.

--- Content provided by‌ FirstRanker.com ---

15. its is never safe to take published statistics at their face value without

knowing their meaning and limitations. Elucidate this statement by
enumerating and explaining the various points which you would consider
before using any published data. Illustrate your answer by examples

--- Content provided by‍ FirstRanker.com ---

wherever possible.



G.Thamizh chelvan

--- Content provided by FirstRanker.com ---


S.G.Lecturer in commerce and International Business


Dr.G.R.D.Col ege of science

--- Content provided by‍ FirstRanker.com ---


Avinashi road

Coimbatore

--- Content provided by⁠ FirstRanker.com ---


UNIT V - MARKETING RESEARCH



--- Content provided by FirstRanker.com ---

CHAPTER I



Data Analysis ? Univariate Analysis

--- Content provided by‍ FirstRanker.com ---




Objective:

--- Content provided by​ FirstRanker.com ---

The objective of this chapter is to understand:

Methods of analysing Market Research data
Methods of Univariate Analysis

--- Content provided by​ FirstRanker.com ---

Introduction:



After collection of data from marketing research, the data has to be analyzed.

--- Content provided by⁠ FirstRanker.com ---


This can be carried out by various statistical methods.



--- Content provided by⁠ FirstRanker.com ---

Data analysis begins with univariate analysis. Univariate analysis also is the

foundation for the bivariate and multivariate analysis.


--- Content provided by‍ FirstRanker.com ---


Univariate analysis is the assessment of the distributional properties of a

variable. It serves two broad purposes: description and preparation for

--- Content provided by‌ FirstRanker.com ---

multivariate analysis. These functions correspond to the two primary forms of

univariate analysis, the assessment of central tendency and of dispersion, or

convergence and divergence. This mainly deals with the meaning of a typical

--- Content provided by FirstRanker.com ---


value and to what extent do values differ from this typical value. Descriptive

research focuses on identifying what is most characteristic of a set of

--- Content provided by⁠ FirstRanker.com ---


observations. Any variation from this typical value usually is the most important

concern with regard to subsequent multivariate analysis.

--- Content provided by‌ FirstRanker.com ---



There is a possibility that many times univariate analysis itself is the research

goal. For example, we might calculate the percentage of women going for work.

--- Content provided by FirstRanker.com ---


Descriptive research emphasizes what are most typical using estimates of central

tendency.

--- Content provided by⁠ FirstRanker.com ---



When univariate analysis is preliminary to multivariate analysis, dispersion

takes center stage. This analysis often uncovers at least some technical problems

--- Content provided by‍ FirstRanker.com ---


that need to be resolved before other forms of analysis can proceed.



--- Content provided by FirstRanker.com ---

Measures of Central Tendency



Measures of central tendency summarize the entire distribution of values as one

--- Content provided by‍ FirstRanker.com ---


single quantity or quality that can be thought of as the average value. Measures

of central tendency are measures of the location of the middle or the center of a

--- Content provided by⁠ FirstRanker.com ---

distribution. The mean is the most commonly used measure of central tendency.



The three most commonly-used measures of central tendency are:

--- Content provided by FirstRanker.com ---


1. Mean

a. Arithmetic Mean

--- Content provided by⁠ FirstRanker.com ---

The arithmetic mean is commonly called the average. The sum of the

values divided by the number of values--often called the "average."

The mean is the sum of all the scores divided by the number of

--- Content provided by FirstRanker.com ---


scores.


This is denoted as

--- Content provided by​ FirstRanker.com ---


= X/N

where is the population mean and N is the number of scores. If the

--- Content provided by⁠ FirstRanker.com ---

scores are from a sample, then the symbol M refers to the mean and

N refers to the sample size. The formula for M is the same as the

formula for .

--- Content provided by⁠ FirstRanker.com ---


Example: The mean of 5, 10, 22, 25, 17 is (5 + 10 + 22 + 25 + 17) / 5

= 15.8.

--- Content provided by‌ FirstRanker.com ---

The mean is a good measure of central tendency for roughly

symmetric distributions. This can be misleading in skewed

distributions since it can be greatly influenced by extreme scores.

--- Content provided by‍ FirstRanker.com ---


Therefore, other statistics such as the median may be more

informative for distributions such as reaction time or family income

--- Content provided by‍ FirstRanker.com ---

that are frequently much skewed.

b. Geometric Mean

The geometric mean is the nth root of the product of the scores.

--- Content provided by⁠ FirstRanker.com ---


Thus, the geometric mean of the scores: 1, 2, 3, and 10 is the fourth

root of 1 x 2 x 3 x 10 which is the fourth root of 60 which equals

--- Content provided by⁠ FirstRanker.com ---

2.78. The formula can be written as:

Geometric mean =


--- Content provided by FirstRanker.com ---


where X means to take the product of all the values of X.


The geometric mean can also be computed by:

--- Content provided by FirstRanker.com ---


1. taking the logarithm of each number

2. computing the arithmetic mean of the logarithms

--- Content provided by⁠ FirstRanker.com ---

3. raising the base used to take the logarithms to the arithmetic

mean.

c. Harmonic Mean

--- Content provided by​ FirstRanker.com ---


The harmonic mean is used to take the mean of sample sizes. If there

are k samples each of size n, then the harmonic mean is defined as:

--- Content provided by‌ FirstRanker.com ---



For the numbers 1, 2, 3, and 10, the harmonic mean is:


--- Content provided by⁠ FirstRanker.com ---


= 2.069. This is less than the geometric mean of 2.78 and the

arithmetic mean of 4.

--- Content provided by​ FirstRanker.com ---

The arithmetic mean in the case of a frequency distribution is calculated using

the following steps:


--- Content provided by⁠ FirstRanker.com ---


The middle point of each class interval is found and is multiplied by the

number of observations (frequencies) in that class.

--- Content provided by‌ FirstRanker.com ---

The resultant values are summed up.
The total is divided by the number of observations.



--- Content provided by⁠ FirstRanker.com ---


h
fix

i i

--- Content provided by‌ FirstRanker.com ---


x

X = i=1

--- Content provided by‌ FirstRanker.com ---

=

n

where,

--- Content provided by​ FirstRanker.com ---




X = the sample mean

--- Content provided by‌ FirstRanker.com ---

fi = the frequency of the i th class
xi= the mid-point of the i th class
h = the number of classes

n= the total number of observations in the sample

--- Content provided by‌ FirstRanker.com ---




2. Median

--- Content provided by‌ FirstRanker.com ---

The median is the middle score of a distribution: half the scores are above

the median and half are below the median. The median is less sensitive to

extreme scores than the mean and this makes it a better measure than the

--- Content provided by‌ FirstRanker.com ---


mean for highly skewed distributions. The median income is usually more

informative than the mean income, for example.

--- Content provided by‍ FirstRanker.com ---

Example: The median of the same five numbers (5, 10, 22, 25, and 17) is 17.

The sum of the absolute deviations of each number from the median is lower

than is the sum of absolute deviations from any other number. The mean,

--- Content provided by FirstRanker.com ---


median, and mode are equal in symmetric distributions. The mean is higher

than the median in positively skewed distributions and lower than the

--- Content provided by FirstRanker.com ---

median in negatively skewed distributions

For a grouped series, the median is calculated as:


--- Content provided by FirstRanker.com ---



l -l

-

--- Content provided by‌ FirstRanker.com ---


M =

M l

--- Content provided by⁠ FirstRanker.com ---

= + 2 1

+

(m

--- Content provided by⁠ FirstRanker.com ---


( -

m c

--- Content provided by FirstRanker.com ---

- )

c

1

--- Content provided by‌ FirstRanker.com ---


f



--- Content provided by FirstRanker.com ---

where,

M = Median

l1 = the lower limit of the class in which the median lies

--- Content provided by‍ FirstRanker.com ---


l2 = the upper limit of the class in which the median lies
f = the frequency of the class in which the median lies

m = the middle item or n/2

--- Content provided by⁠ FirstRanker.com ---


c = the cumulative frequency of the class preceding the one in which the median

lies.

--- Content provided by FirstRanker.com ---



3. Mode


--- Content provided by FirstRanker.com ---


The third common measure of central tendency is the mode. The advantage

of the mode as a measure of central tendency is that its meaning is obvious.

--- Content provided by‍ FirstRanker.com ---

Further, it is the only measure of central tendency that can be used with

nominal data.


--- Content provided by‌ FirstRanker.com ---


Some of the important characteristics of the mode are:

It can be applied to both qualitative and quantitative distribution
It is not affected by the extreme values in the distribution

--- Content provided by FirstRanker.com ---

It can be ascertained in an open-ended distribution

Mode denotes the most frequently-occurring value (or values). The mode is

the value (or values) with the highest frequency.

--- Content provided by⁠ FirstRanker.com ---



Example: For men having the following ages -- 19, 18, 21, 23, 23, 23, 24

and 21, the mode is 23.

--- Content provided by‍ FirstRanker.com ---


In case of a grouped data, the mode is calculated using the following

formula:

--- Content provided by‌ FirstRanker.com ---



f -f

-

--- Content provided by⁠ FirstRanker.com ---


1 0

Mode = l

--- Content provided by‌ FirstRanker.com ---

M

+

X i

--- Content provided by​ FirstRanker.com ---


X

1

--- Content provided by‌ FirstRanker.com ---

(f -f

- ) ?

) (f -f

--- Content provided by FirstRanker.com ---


- )

1 0

--- Content provided by‌ FirstRanker.com ---

1 2




--- Content provided by FirstRanker.com ---


where,

l1 = the lower value of the class in which the mode lies
f1 = the frequency of the class in which the mode lies

--- Content provided by⁠ FirstRanker.com ---

f0 = the frequency of the class preceding the modal class

f2 = the frequency of the class succeeding the modal class
i = the class interval of the modal class

--- Content provided by‍ FirstRanker.com ---

The mode is greatly subject to sample fluctuations and is therefore not

recommended to be used as the only measure of central tendency. A further

disadvantage of the mode is that many distributions have more than one mode.

--- Content provided by FirstRanker.com ---


These distributions are called "multimodal." In contrast to the mode, the median

and the mean both pertain exclusively to ordered data.

--- Content provided by‍ FirstRanker.com ---

The choice of a measure of central tendency depends upon the level of

measurement (nominal, ordinal, interval, or ratio) of the variable and the shape

of its distribution. The mode is the only indicator of central tendency for a

--- Content provided by‌ FirstRanker.com ---


nominal variable. It may be computed for other types of variables as well, but is

not especially useful unless there is a distinct peak, that is, when one value

--- Content provided by​ FirstRanker.com ---

clearly predominates. At least an ordinal level of measurement is required for

the median; the mean additionally requires an interval level of measurement. In

general, the mean is preferred over the median and the median over the mode

--- Content provided by‍ FirstRanker.com ---


because the mean utilizes the most information about the distribution whereas

the mode preserves only one piece of information. This also depends on the

--- Content provided by⁠ FirstRanker.com ---

manner in which the variable is distributed.



It is necessary to examine the entire set of values to determine which value best

--- Content provided by⁠ FirstRanker.com ---


typifies the set as a whole. It is inadvisable to calculate a measure of central

tendency for a variable without first examining its distribution.

--- Content provided by FirstRanker.com ---



Dispersion


--- Content provided by​ FirstRanker.com ---


As seen earlier, the measures of central tendency are used to estimate "normal"

values of a dataset. Measures of dispersion are important for describing the

--- Content provided by‌ FirstRanker.com ---

spread of the data, or its variation around a central value. Two distinct samples

may have the same mean or median, but completely different levels of

variability, or vice versa. A proper description of a set of data should include

--- Content provided by‌ FirstRanker.com ---


both of these characteristics. There are various methods that can be used to

measure the dispersion of a dataset, each with its own set of advantages and

--- Content provided by⁠ FirstRanker.com ---

disadvantages.

1. Range

It`s calculation is one of the simplest. It is defined as the difference between the

--- Content provided by‌ FirstRanker.com ---


largest and smallest sample values. The range depends only on extreme values

and provides no information about how the remaining data is distributed.

--- Content provided by​ FirstRanker.com ---

2. Variance and Standard Deviation


The standard deviation is the square root of the sample variance. These

--- Content provided by‍ FirstRanker.com ---

measures of dispersion are very important.



What the formula means:

--- Content provided by​ FirstRanker.com ---


(1) xr - means take each value in turn and subtract the mean from each value.
(2) (xr - )? means square each of the results obtained from step (1). This is to
get rid of any minus signs.

--- Content provided by‌ FirstRanker.com ---

(3) (xr - )? means add up all of the results obtained from step (2).
(4) Divide step (3) by n, which is the sum of the numbers

(5) For the standard deviation, square root the answer to step (4).

--- Content provided by⁠ FirstRanker.com ---

Grouped Data

The formula for the standard deviation when the data is grouped is:


--- Content provided by​ FirstRanker.com ---





Example:

--- Content provided by‌ FirstRanker.com ---


Find out the variance for the following. The table shows scores (out of 10)

obtained by 20 people in a test

--- Content provided by‍ FirstRanker.com ---

Scores (x) Frequency (f)

1

0

--- Content provided by‌ FirstRanker.com ---


2

1

--- Content provided by‌ FirstRanker.com ---

3

1

4

--- Content provided by​ FirstRanker.com ---


3

5

--- Content provided by⁠ FirstRanker.com ---

2

6

5

--- Content provided by‌ FirstRanker.com ---


7

5

--- Content provided by⁠ FirstRanker.com ---

8

2

9

--- Content provided by⁠ FirstRanker.com ---


0

10

--- Content provided by FirstRanker.com ---

1




--- Content provided by⁠ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---





Solution:

--- Content provided by‍ FirstRanker.com ---


Frequency

Scores (x) (f)

--- Content provided by​ FirstRanker.com ---

fx

fx2

1

--- Content provided by⁠ FirstRanker.com ---


0

0

--- Content provided by​ FirstRanker.com ---

0

2

1

--- Content provided by​ FirstRanker.com ---


2

4

--- Content provided by‌ FirstRanker.com ---

3

1

3

--- Content provided by FirstRanker.com ---


9

4

--- Content provided by​ FirstRanker.com ---

3

12

48

--- Content provided by​ FirstRanker.com ---


5

2

--- Content provided by FirstRanker.com ---

10

50

6

--- Content provided by⁠ FirstRanker.com ---


5

30

--- Content provided by⁠ FirstRanker.com ---

180

7

5

--- Content provided by⁠ FirstRanker.com ---


35

245

--- Content provided by​ FirstRanker.com ---

8

2

16

--- Content provided by​ FirstRanker.com ---


128

9

--- Content provided by‍ FirstRanker.com ---

0

0

0

--- Content provided by‌ FirstRanker.com ---


10

1

--- Content provided by‍ FirstRanker.com ---

10

100


--- Content provided by FirstRanker.com ---


20

118

--- Content provided by​ FirstRanker.com ---

764




--- Content provided by‍ FirstRanker.com ---

Variance = 764 - (118)?



20 ( 20 )

--- Content provided by‍ FirstRanker.com ---


= 38.2 - 34.81 = 3.39



--- Content provided by FirstRanker.com ---





Summary:

--- Content provided by‍ FirstRanker.com ---




The chapter dealt with the measures of central tendency which are the arithmetic

--- Content provided by‍ FirstRanker.com ---

mean, the median and the mode. This was followed by the measures of

dispersion; the standard deviation and the coefficient of variation.


--- Content provided by‍ FirstRanker.com ---


The measures of central tendency are used to estimate "normal" values of a

dataset. Measures of dispersion are important for describing the spread of the

--- Content provided by‍ FirstRanker.com ---

data, or its variation around a central value. Two distinct samples may have the

same mean or median, but completely different levels of variability, or vice

versa.

--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---

Questions:




--- Content provided by FirstRanker.com ---

1. What are the measures of central tendency?

2. What is a mean? Explain the various forms of mean.

3. What are the characteristics of the median?

--- Content provided by‍ FirstRanker.com ---


4. What are the characteristics of the mode?

5. What are the measures of the central tendency?

--- Content provided by​ FirstRanker.com ---

6. Explain standard deviation.

7. How you measure variance?

8. How are the measures of central tendency different from the measures of

--- Content provided by FirstRanker.com ---


dispersion?



--- Content provided by‍ FirstRanker.com ---





CHAPTER II

--- Content provided by⁠ FirstRanker.com ---


HYPOTHESIS TESTING

Objective:

--- Content provided by⁠ FirstRanker.com ---

The objective of this chapter is to understand:

Meaning of hypothesis
Hypothesis testing
Types of hypothesis

--- Content provided by‌ FirstRanker.com ---

Two types of error in hypothesis testing
One-tailed and two-tailed tests

Introduction:

--- Content provided by⁠ FirstRanker.com ---


A statistical hypothesis is an assumption about a population parameter. This

assumption may or may not be true.

--- Content provided by‍ FirstRanker.com ---

The best way to determine whether a statistical hypothesis is true is to examine

the entire population. Since this is often impractical, researchers typically

examine a random sample from the population. If the sample data are consistent

--- Content provided by⁠ FirstRanker.com ---


with the statistical hypothesis, the hypothesis is accepted; if not, the hypothesis

is rejected.

--- Content provided by‌ FirstRanker.com ---

There are two types of statistical hypothesis.

Null hypothesis. The null hypothesis is usually the hypothesis that

sample observations result purely from chance effects.

--- Content provided by‌ FirstRanker.com ---


Alternative hypothesis. The alternative hypothesis is the hypothesis that

sample observations are influenced by some non-random cause.

--- Content provided by‍ FirstRanker.com ---

For example, suppose we wanted to determine whether a coin was fair and

balanced. A null hypothesis might be that half the flips would result in Heads

and half, in Tails. The alternative hypothesis might be that the number of Heads

--- Content provided by​ FirstRanker.com ---


and Tails would be very different. Suppose we flipped the coin 50 times,

resulting in 40 Heads and 10 Tails. Given this result, we would be inclined to

--- Content provided by FirstRanker.com ---

reject the null hypothesis and accept the alternative hypothesis.

The term null means nothing or invalid. It may be written as:

H0: = 0

--- Content provided by FirstRanker.com ---


Where, H0 is the null hypothesis and 0 is the mean of the population.

The alternative hypothesis is

--- Content provided by‍ FirstRanker.com ---

HA: 0

The rejection of the null hypothesis will show that the mean of the population is

not 0. If this happens, then it implies that the alternative hypothesis is accepted.

--- Content provided by⁠ FirstRanker.com ---

There can be more than two or more alternative hypothesis though only one can

be tested at a time against the null hypothesis.

Hypothesis Testing

--- Content provided by‌ FirstRanker.com ---


Statisticians follow a formal process to determine whether to accept or reject a

null hypothesis, based on sample data. This process, called hypothesis testing,

--- Content provided by FirstRanker.com ---

consists of four steps.

Formulating the hypothesis: The first step in hypothesis testing is to

formulate the hypothesis to be tested. This means stating the null

--- Content provided by FirstRanker.com ---


hypothesis and the alternative hypothesis.

Identifying the test statistic: The test statistic is a statistic that will be

--- Content provided by FirstRanker.com ---

used by the researcher to determine whether the null hypothesis should

be accepted or rejected. Typically, the test statistic is the sample estimate

of the population parameter in the null hypothesis. Therefore, since we

--- Content provided by‌ FirstRanker.com ---


are testing a hypothesis about a population mean, the test statistic will be

the sample mean. When the hypothesis pertains to a large sample (30 or

--- Content provided by‌ FirstRanker.com ---

more), the z-test implying normal distribution is used. When a sample is

small (less than 30), the use of the z-test will be inappropriate. Instead

the t-test will be more suitable. The test criteria frequently used in

--- Content provided by FirstRanker.com ---


hypothesis testing are Z, t. F and 2.

Formulating a decision rule: The decision rule consists of two parts:

--- Content provided by​ FirstRanker.com ---

(1) a test statistic and (2) a range of values, called the region of


acceptance. The decision rule determines whether a null hypothesis is

--- Content provided by​ FirstRanker.com ---

accepted or rejected. If the test statistic falls within the region of

acceptance, the null hypothesis is accepted; otherwise, it is rejected.

Accepting or rejecting the null hypothesis: Once the region of

--- Content provided by‌ FirstRanker.com ---


acceptance is defined, the null hypothesis can be tested against sample

data. The test statistic is computed. For example consider that the test

--- Content provided by‍ FirstRanker.com ---

statistic is the sample mean. If the sample mean falls within the region of

acceptance, the null hypothesis is accepted; if not, it is rejected.

Decision Rules

--- Content provided by​ FirstRanker.com ---


There are four possibilities that can arise when a hypothesis is tested:

1. The hypothesis is true but our test leads to its rejection.

--- Content provided by‍ FirstRanker.com ---

2. The hypothesis is false but our test leads to its acceptance.

3. The hypothesis is true and our test leads to its acceptance.

4. The hypothesis is false and our test leads to its rejection.

--- Content provided by‌ FirstRanker.com ---


Out of these four, the first two lead to an error in decision. The first possibility

leads to a Type I error and the second possibility leads to a Type II error. This

--- Content provided by‍ FirstRanker.com ---

can be shown as follows:

STAT

ST

--- Content provided by‌ FirstRanker.com ---


E

AT OF

--- Content provided by​ FirstRanker.com ---

O

F NATU

N

--- Content provided by‍ FirstRanker.com ---


R

ATU E

--- Content provided by‌ FirstRanker.com ---

R

H Tru

r e

--- Content provided by‌ FirstRanker.com ---


u

H Fa

--- Content provided by⁠ FirstRanker.com ---

F lse

a

o

--- Content provided by‌ FirstRanker.com ---


o

Cor

--- Content provided by‌ FirstRanker.com ---

Co r

r e

r c

--- Content provided by​ FirstRanker.com ---


e t tRe



--- Content provided by FirstRanker.com ---

t

Re en

e t

--- Content provided by‍ FirstRanker.com ---


n io

t n

--- Content provided by​ FirstRanker.com ---

Typ

y e

p

--- Content provided by FirstRanker.com ---


e III IEr

r

--- Content provided by FirstRanker.com ---

Er or

Ret

Re a

--- Content provided by‌ FirstRanker.com ---


t in

a

--- Content provided by⁠ FirstRanker.com ---

in H

o

Ho

--- Content provided by FirstRanker.com ---


DEC

D

--- Content provided by⁠ FirstRanker.com ---

I

EC SI

I ON

--- Content provided by​ FirstRanker.com ---


O

Typ

--- Content provided by FirstRanker.com ---

y e

p

e I IEr

--- Content provided by‌ FirstRanker.com ---


r

Er or

--- Content provided by‍ FirstRanker.com ---

o

Cor

Co r

--- Content provided by FirstRanker.com ---


r e

r c

--- Content provided by‌ FirstRanker.com ---

e t tRe



j

--- Content provided by‍ FirstRanker.com ---


Re ec

e t

--- Content provided by‍ FirstRanker.com ---

c io

t n

Reje

--- Content provided by‌ FirstRanker.com ---


Re c

je t

--- Content provided by​ FirstRanker.com ---

c tH

io

Ho

--- Content provided by​ FirstRanker.com ---





The decision rule is a procedure that a researcher uses to decide whether to

--- Content provided by‌ FirstRanker.com ---


accept or reject the null hypothesis. There are two types of errors that can result

from a decision rule.

--- Content provided by‍ FirstRanker.com ---

Type I error. A Type I error occurs when the researcher rejects a null

hypothesis when it is true. The probability of committing a Type I error

is called the significance level. This probability is also called alpha, and

--- Content provided by‍ FirstRanker.com ---


is often denoted by .

Type II error. A Type II error occurs when the researcher accepts a null

--- Content provided by​ FirstRanker.com ---

hypothesis that is false. The probability of committing a Type II error is

called Beta, and is often denoted by . The probability of not committing

a Type II error is called the Power of the test.

--- Content provided by​ FirstRanker.com ---


In practice, the decision rule has two parts: (1) a test statistic and (2) a range of

values. The range of values is called the region of acceptance. The region of

--- Content provided by⁠ FirstRanker.com ---

acceptance is defined so that the chance of making a Type I error is equal to the

significance level. If the test statistic falls within the region of acceptance, the

null hypothesis is accepted.

--- Content provided by‍ FirstRanker.com ---


Note: The set of values outside the region of acceptance is called the region of

rejection. If the test statistic falls within the region of rejection, the null

--- Content provided by​ FirstRanker.com ---

hypothesis is rejected. In such cases, we say that the hypothesis has been

rejected at the level of significance.

One-Tailed and Two-Tailed Tests

--- Content provided by‍ FirstRanker.com ---


To understand the difference between these look at the table below. It shows

three sets of hypothesis. Each makes a statement about how the population mean

--- Content provided by​ FirstRanker.com ---

is related to a specified value M.

Set Null

Alternative Number of

--- Content provided by​ FirstRanker.com ---


hypothesis hypothesis tails

1

--- Content provided by FirstRanker.com ---

= M

M

2

--- Content provided by⁠ FirstRanker.com ---


2

> M

--- Content provided by⁠ FirstRanker.com ---

< M

1

3

--- Content provided by FirstRanker.com ---


< M

> M

--- Content provided by‍ FirstRanker.com ---

1

The first set of hypotheses (Set 1) is an example of a two-tailed test, since an

extreme value on either side of the sampling distribution would cause a

--- Content provided by FirstRanker.com ---


researcher to reject the null hypothesis. The other two sets of hypotheses (Sets 2

and 3) are one-tailed tests, since an extreme value on only one side of the

--- Content provided by⁠ FirstRanker.com ---

sampling distribution would cause a researcher to reject the null hypothesis.

A test of a statistical hypothesis, where the region of rejection is on only one

side of the sampling distribution, is called a one-tailed test. For example,

--- Content provided by‍ FirstRanker.com ---


suppose the null hypothesis states that the mean is less than or equal to 10. The

alternative hypothesis would be that the mean is greater than 10. The region of

--- Content provided by FirstRanker.com ---

rejection would consist of a range of numbers located on the right side of

sampling distribution; that is, a set of numbers greater than 10.

A test of a statistical hypothesis, where the region of rejection is on both sides of

--- Content provided by FirstRanker.com ---


the sampling distribution, is called a two-tailed test. For example, suppose the

null hypothesis states that the mean is equal to 10. The alternative hypothesis

--- Content provided by​ FirstRanker.com ---

would be that the mean is less than 10 or greater than 10. The region of rejection

would consist of a range of numbers located on both sides of sampling

distribution; that is, the region of rejection would consist partly of numbers that

--- Content provided by FirstRanker.com ---


were less than 10 and partly of numbers that were greater than 10.


Other Considerations

--- Content provided by‍ FirstRanker.com ---


There may be other considerations to be made while testing the null hypothesis.

These are:

--- Content provided by FirstRanker.com ---

Assumptions need to be made about the sampling distribution of the

mean score. If the sample is relatively large (i.e., greater than or equal to

30), you can assume, based on the central limit theorem, that the

--- Content provided by FirstRanker.com ---


sampling distribution will be roughly normal.

On the other hand, if the sample size is small (less than 30) and if the

--- Content provided by‌ FirstRanker.com ---

population random variable is approximately normally distributed (i.e., has a

bell-shaped curve), you can transform the mean score into a t score. The t

score will have a t distribution.

--- Content provided by‌ FirstRanker.com ---


Assume that the mean of the sampling distribution is equal to the test

value M specified in the null hypothesis.

--- Content provided by‍ FirstRanker.com ---

In some situations, the standard deviation needs to be computed from the

sampling distribution sx. If the standard deviation of the population is

known, then

--- Content provided by‌ FirstRanker.com ---


sx = * sqrt[( 1/n ) - ( 1/N )]

where n is the sample size and N is the population size. On the other

--- Content provided by‍ FirstRanker.com ---

hand, if the standard deviation of the population is unknown, then

sx = s * sqrt[( 1/n ) - ( 1/N )]

where s is the sample standard deviation.

--- Content provided by FirstRanker.com ---



Hypothesis testing in respect of interval data:

1. Test of sample mean (Single population):

--- Content provided by​ FirstRanker.com ---


On the basis of the sample drawn from the population one needs to infer about

the population parameter which could be the population mean. We need to carry

--- Content provided by‍ FirstRanker.com ---

out an appropriate statistical test of significance for testing the hypothesis

concerning the population mean. We can consider two cases, sample size being

large (n>30) and sample size small (n30).

--- Content provided by‌ FirstRanker.com ---


If n is large, the sample distribution of mean follows normal distribution as per

central limit theorem and we can go for Z test. However, when sample size is

--- Content provided by‍ FirstRanker.com ---

small, we may have to choose between Z and t test depending upon whether

standard deviation () is known or not. In case is known, we should go for Z

test or t test.

--- Content provided by FirstRanker.com ---


In case of a normal distribution of sample means (x bar) with mean and

standard deviation is represented by

--- Content provided by FirstRanker.com ---

=

= / n

x

--- Content provided by​ FirstRanker.com ---




The standard normal distribution is calculated as:

--- Content provided by‌ FirstRanker.com ---

x -

Z =

x

--- Content provided by​ FirstRanker.com ---




This is used for testing the hypothesis.

--- Content provided by⁠ FirstRanker.com ---

2. Test of Proportion:


In order to test the hypothesis that population proportion (P) takes a specified

--- Content provided by⁠ FirstRanker.com ---

value Po against a two sided alternative, we test the hypothesis as follows:

Ho (Null Hypothesis): = o

H1 (Alternative Hypothesis): o

--- Content provided by‌ FirstRanker.com ---


Here it can be shown that:

E (P) = and

--- Content provided by‌ FirstRanker.com ---

(1-)

=

P

--- Content provided by‍ FirstRanker.com ---


n



--- Content provided by⁠ FirstRanker.com ---

Using the Z-test, we find that

P -

Z =

--- Content provided by​ FirstRanker.com ---


P



--- Content provided by‌ FirstRanker.com ---

Summary:

A statistical hypothesis is an assumption about a population parameter. This

assumption may or may not be true.

--- Content provided by FirstRanker.com ---


There are two types of statistical hypothesis.

Null hypothesis. The null hypothesis is usually the hypothesis that

--- Content provided by⁠ FirstRanker.com ---

sample observations result purely from chance effects.


Alternative hypothesis. The alternative hypothesis is the hypothesis that

--- Content provided by‍ FirstRanker.com ---

sample observations are influenced by some non-random cause.

This process, called hypothesis testing, consists of four steps: Formulating the

hypothesis, identifying the test statistic, formulating a decision rule and

--- Content provided by‌ FirstRanker.com ---


accepting or rejecting the null hypothesis

There are two types of errors that can result from a decision rule: Type I error

--- Content provided by‍ FirstRanker.com ---

which occurs when the researcher rejects a null hypothesis when it is true and

Type II error which occurs when the researcher accepts a null hypothesis that is

false.

--- Content provided by FirstRanker.com ---


A test of a statistical hypothesis, where the region of rejection is on only one

side of the sampling distribution, is called a one-tailed test. A test of a statistical

--- Content provided by‍ FirstRanker.com ---

hypothesis, where the region of rejection is on both sides of the sampling

distribution, is called a two-tailed test.

Questions:

--- Content provided by⁠ FirstRanker.com ---


1. What is a hypothesis? Explain.

2. Differentiate between Null hypothesis and alternative hypothesis.

--- Content provided by​ FirstRanker.com ---

3. What are the steps involved in testing a hypothesis?

4. Is hypothesis testing useful in marketing decision making?

5. What are Type I error and Type II errors?

--- Content provided by​ FirstRanker.com ---


6. Explain the relationship between Type I and Type II errors.

7. What are one-tailed and two-tailed tests?

--- Content provided by‌ FirstRanker.com ---

8. What are the other considerations to be made while testing the null

hypothesis?

9. How will you test the sample mean from a single population?

--- Content provided by‌ FirstRanker.com ---



10. How will you test the hypothesis of a population proportion?


--- Content provided by⁠ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---






--- Content provided by‍ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---


CHAPTER III



--- Content provided by‍ FirstRanker.com ---

Bivariate Analysis



Objective:

--- Content provided by‌ FirstRanker.com ---




The objective of this chapter is to understand:

--- Content provided by FirstRanker.com ---

Association between Dependent Variable (DV) and Independent

Variable (IV).

Importance and methodology of correlation analysis.

--- Content provided by‍ FirstRanker.com ---

Importance and methodology of regression analysis.




--- Content provided by⁠ FirstRanker.com ---

Introduction:



In bivariate analysis, the hypothesis of "association" and causality are tested. In

--- Content provided by‍ FirstRanker.com ---


its simplest form, association simply refers to the extent to which it becomes

easier to know/predict a value for the Dependent Variable (DV) if we know a

--- Content provided by​ FirstRanker.com ---

case's value on the Independent Variable (IV).



This association could be understood by a measure of association. A measure of

--- Content provided by‍ FirstRanker.com ---


association often ranges between ?1 and 1. Where the sign of the integer

represents the "direction" of correlation (negative or positive relationships) and

--- Content provided by‍ FirstRanker.com ---

the distance away from 0 represents the degree or extent of correlation ? the

farther the number away from 0, the higher or "more perfect" the relationship is

between the IV and DV.

--- Content provided by FirstRanker.com ---




Measures of association and statistical significance that are used vary by the

--- Content provided by‍ FirstRanker.com ---

level of measurement of the variables analyzed.

For Nominal Variables:


--- Content provided by​ FirstRanker.com ---


Measure of association is Lambda



--- Content provided by‌ FirstRanker.com ---

The formula for Lambda is



(Reduction in Error from guessing to predicting based on IV)

--- Content provided by⁠ FirstRanker.com ---


Number of Original Error



--- Content provided by​ FirstRanker.com ---


This gives a ratio of how much improvement your prediction has by knowing

values on the IV. Lambda ranges from 0 to 1. The higher the number, the

--- Content provided by‌ FirstRanker.com ---

stronger the relationship between the two variables.



The measure of statistical significance for nominal variables (and limited scale

--- Content provided by⁠ FirstRanker.com ---


ordinal variables) is Chi Square. In fact, Chi Square can measure the statistical

significance of any crosstab. It tells us how different the values in the cells of a

--- Content provided by⁠ FirstRanker.com ---

crosstab are from expected values (or values predicted if no real relationship

between the two variables existed ? uses marginals to calculate these expected

values).

--- Content provided by FirstRanker.com ---




The Chi Square is based on these factors:

--- Content provided by​ FirstRanker.com ---

1. The distribution of cases among the cells (can show the extent to which

differences are observed;

2. The number of cells (degrees of freedom), and

--- Content provided by‌ FirstRanker.com ---


3. The size of the sample (n).



--- Content provided by‌ FirstRanker.com ---

The Chi Square requires the following steps:

1. State the null hypothesis and calculate the number in each category

assuming that the null hypothesis is correct.

--- Content provided by‌ FirstRanker.com ---


2. Determine the level of significance.

3. Calculate the Chi Square (x2) as follows

--- Content provided by⁠ FirstRanker.com ---



k (O

(

--- Content provided by‍ FirstRanker.com ---


? E )2

)

--- Content provided by⁠ FirstRanker.com ---

i

i

X2

--- Content provided by‍ FirstRanker.com ---


X =

i=1

--- Content provided by‍ FirstRanker.com ---

Ei



Where, Oi is the observed frequency in the ith category

--- Content provided by‌ FirstRanker.com ---




Ei is the expected frequency in the ith category

--- Content provided by FirstRanker.com ---




k is the number of categories

--- Content provided by⁠ FirstRanker.com ---

4. Determine the number of degrees of freedom. For the specified level of

significance and the degrees of freedom, find the critical or theoretical

value of x2.

--- Content provided by FirstRanker.com ---


5. The calculated value of the x2 is then calculated with the theoretical

value of x2 and the region of rejection is determined.

--- Content provided by​ FirstRanker.com ---



For ordinal variables:


--- Content provided by FirstRanker.com ---


The appropriate measures of association all attempt to measure how values of

ordered variables relate for the sample of cases. For instance, how many times

--- Content provided by‌ FirstRanker.com ---

high values are associated with high values, how many times are they associated

with low values. They each use discordant and concordant pairs to create a

value between ?1 and 1. O indicates no relationship between how the values for

--- Content provided by‍ FirstRanker.com ---


the cases pair up. The closer to ?1 means the stronger the negative (inverse)

relationship, and the closer to 1 the more "perfect" the positive relationship.

--- Content provided by‍ FirstRanker.com ---



There are several measures of association which measure ordinal variables'

relationships. Somer's d, tau b, tau c, and gamma are the most usual ones. All

--- Content provided by FirstRanker.com ---


are slight variations of the formula related in layman's terms above. While

Somer's d, tau b, and tau c will all have very close to the same value, gamma

--- Content provided by​ FirstRanker.com ---

usually will appear to have a slightly higher (stronger) relationship.




--- Content provided by⁠ FirstRanker.com ---


For interval variables



--- Content provided by‌ FirstRanker.com ---

Regression and correlation analysis are used for this. The two terms correlation

and regression are distinct from each other and many times are used

interchangeably. Correlation is a statistical technique used for measuring the

--- Content provided by​ FirstRanker.com ---


relationship or interdependence of two or more variables. Correlation does not

necessarily indicate a causal relationship between two or more variables.

--- Content provided by‍ FirstRanker.com ---

Regression analysis refers to the technique for deriving an equation that relates

the dependent variable to one or more variables. It is used to predict one variable

on the basis of another and hence helps in bringing out the causal relationship

--- Content provided by‍ FirstRanker.com ---


between two or more variables.



--- Content provided by⁠ FirstRanker.com ---

Correlation Analysis:



Correlation is a statistical technique used for measuring the relationship or

--- Content provided by FirstRanker.com ---


interdependence of two or more variables. The measurement scales used should

be at least interval scales, but other correlation coefficients are available to

--- Content provided by​ FirstRanker.com ---

handle other types of data. Correlation coefficients can range from -1.00 to

+1.00. The value of -1.00 represents a perfect negative correlation while a value

of +1.00 represents a perfect positive correlation. A value of 0.00 represents a

--- Content provided by‌ FirstRanker.com ---


lack of correlation.



--- Content provided by‍ FirstRanker.com ---

In statistics, the Correlation coefficient (r) is a measure of how well a linear

equation describes the relation between two variables X and Y measured on the

same object or organism. It is defined as the sum of the products of the standard

--- Content provided by​ FirstRanker.com ---


scores of the two measures divided by the degrees of freedom:



--- Content provided by‍ FirstRanker.com ---





The result obtained is equivalent to dividing the covariance between the two

--- Content provided by⁠ FirstRanker.com ---


variables by the product of their standard deviations. In general the correlation

coefficient is one of the two square roots (either positive or negative) of the

--- Content provided by​ FirstRanker.com ---

coefficient of determination (r2), which is the ratio of explained variation to total

variation:


--- Content provided by⁠ FirstRanker.com ---




where:

--- Content provided by FirstRanker.com ---



Y = a score on a random variable Y

Y' = corresponding predicted value of Y, given the correlation of X and Y and

--- Content provided by‍ FirstRanker.com ---


the value of X



--- Content provided by​ FirstRanker.com ---

= sample mean of Y (i.e., the mean of a finite number of independent

observed realizations of Y, not to be confused with the expected value of Y)


--- Content provided by​ FirstRanker.com ---


The correlation coefficient adds a sign to show the direction of the relationship.

This applies when the relationship is linear.

--- Content provided by‍ FirstRanker.com ---



The coefficient ranges from -1 to 1. A value of 1 shows that a linear equation

describes the relationship perfectly and positively, with all data points lying on

--- Content provided by​ FirstRanker.com ---


the same line and with Y increasing with X. A score of -1 shows that all data

points lie on a single line but that Y increases as X decreases. A value of 0

--- Content provided by‍ FirstRanker.com ---

shows that a linear model is inappropriate ? that there is no linear relationship

between the variables.


--- Content provided by FirstRanker.com ---


If we have a series of n measurements of X and Y written as xi and yi where i
= 1, 2, ..., n, then the coefficient can be used to estimate the correlation of X and

Y . This is also known as the "sample correlation coefficient". It is especially

--- Content provided by⁠ FirstRanker.com ---


important if X and Y are both normally distributed. The Pearson correlation


coefficient is then the best estimate of the correlation of X and Y . The Pearson

--- Content provided by​ FirstRanker.com ---


correlation coefficient is written:



--- Content provided by⁠ FirstRanker.com ---





where and are the sample means of xi and yi , sx and sy are the sample

--- Content provided by⁠ FirstRanker.com ---

standard deviations of xi and yi and the sum is from i = 1 to n.



This can be written as:

--- Content provided by‍ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---



The absolute value of the sample correlation must be less than or equal to 1


--- Content provided by‍ FirstRanker.com ---


Regression Analysis:

In statistics, regression analysis is used to model relationships between random

--- Content provided by⁠ FirstRanker.com ---

variables, determine the magnitude of the relationships between variables, and

can be used to make predictions based on the models.

Regression analysis models the relationship between one or more response

--- Content provided by‍ FirstRanker.com ---


variables (also called dependent variables) usually named Y, and the predictors

(also called independent variables) usually named X1,...,Xp.

--- Content provided by⁠ FirstRanker.com ---



A line in a two dimensional or two-variable space is defined by the equation

Y=a+b*X; in full text: the Y variable can be expressed in terms of a constant (a)

--- Content provided by​ FirstRanker.com ---



and a slope (b) times the X variable. The constant is also referred to as the

intercept, and the slope as the regression coefficient or B coefficient.

--- Content provided by​ FirstRanker.com ---




Regression analysis can predict the outcome of a given key business indicator

--- Content provided by​ FirstRanker.com ---

(dependent variable) based on the interactions of other related business drivers

(independent variable). For example, it allows predicting sales volume, using the

amount spent on advertising and number of sales people that a company

--- Content provided by​ FirstRanker.com ---


employs.



--- Content provided by​ FirstRanker.com ---

The coefficient of determination, r 2, is useful because it gives the proportion of

the variance (fluctuation) of one variable that is predictable from the other

variable. It is a measure that allows us to determine how certain one can be in

--- Content provided by⁠ FirstRanker.com ---


making predictions from a certain model/graph. The coefficient of determination

is the ratio of the explained variation to the total variation. The coefficient of

--- Content provided by‌ FirstRanker.com ---

determination is such that 0 < r 2 < 1, and denotes the strength of the linear

association between x and y. The coefficient of determination represents the

percent of the data that is the closest to the line of best fit.

--- Content provided by‍ FirstRanker.com ---


Every sample has some variation in it. The total variation is made up of two

parts, the part that can be explained by the regression equation and the part that

--- Content provided by​ FirstRanker.com ---

can't be explained by the regression equation.




--- Content provided by‌ FirstRanker.com ---


In regression analysis, the coefficient of determination is a measure of goodness-

of-fit (i.e. how well or tightly the data fit the estimated model). The coefficient

--- Content provided by‍ FirstRanker.com ---

is defined as the ratio of two sums of squares:




--- Content provided by‍ FirstRanker.com ---

r2 = SSR / SST



where SSR is the sum of squares due to regression, SST is the total sum of

--- Content provided by​ FirstRanker.com ---


squares. By "sum of squares" we mean the sum of squared deviations between

actual values and the mean (SST), or between predicted values and the mean

--- Content provided by​ FirstRanker.com ---

(SSR). The coefficient of determination takes on values between 0 and 1, with

values closer to 1 implying a better fit.


--- Content provided by​ FirstRanker.com ---


The objectives for which market researchers use regression analysis are:

1. Pattern connecting the dependent variable and the independent variable

--- Content provided by FirstRanker.com ---

by establishing a functional relationship between the two.

2. For solving problems involving prediction and forecasting.

3. To study the quantum of variation in the dependent variable using the set

--- Content provided by FirstRanker.com ---


of independent variables.



--- Content provided by FirstRanker.com ---

The Scatter Diagrams:



The Scatter Diagram is a tool for determining the potential correlation between

--- Content provided by FirstRanker.com ---


two different sets of variables, i.e., how one variable changes with the other

variable. This diagram simply plots pairs of corresponding data from two

--- Content provided by​ FirstRanker.com ---

variables. The scatter diagram does not determine the exact relationship

between the two variables, but it does indicate whether they are correlated or

not. It also does not predict cause and effect relationships between these

--- Content provided by​ FirstRanker.com ---


variables.



--- Content provided by‌ FirstRanker.com ---

The scatter diagram is used to:

1) Quickly confirm a hypothesis that two variables are correlated;

2) Provide a graphical representation of the strength of the relationship between

--- Content provided by‍ FirstRanker.com ---


two variables; and

3) Serve as a follow-up step to a cause-effect analysis to establish whether a

--- Content provided by​ FirstRanker.com ---

change in an identified cause can indeed produce a change in its identified

effect.


--- Content provided by‍ FirstRanker.com ---


To make a scatter diagram for two variables requiring confirmation of

correlation, the following simple steps are usually followed:

--- Content provided by‍ FirstRanker.com ---

1) 50-100 pairs of data are collected for this and tabulated;

2) The x- and y-axes of the diagram, along with the scales that

increase to the right for the x-axis and upward for the y-axis are

--- Content provided by FirstRanker.com ---


drawn;

3) The data for one variable is assigned to the x-axis (the

--- Content provided by‍ FirstRanker.com ---

independent variable) and the data for the other variable is

assigned to the y-axis (the independent variable);

4) Plot the data pairs on the scatter diagram, encircling (as many

--- Content provided by‍ FirstRanker.com ---


times as necessary) all data points that are repeated.



--- Content provided by‌ FirstRanker.com ---

Interpretation of the resulting scatter diagram is very simple and can be analyzed

looking at the pattern formed by the points. If the data points plotted on the

scatter diagram are all over the place with no discernible pattern whatsoever,

--- Content provided by FirstRanker.com ---


then there is no correlation at all between the two variables of the scatter

diagram. An example of a scatter diagram that shows no correlation is shown

--- Content provided by FirstRanker.com ---

below




--- Content provided by‌ FirstRanker.com ---



The below scatter diagrams show positive correlation (Strongly positive and

weak positive correlation):

--- Content provided by‍ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---



The below scatter diagrams show negative correlation (Strongly negative and

weak negative correlation):

--- Content provided by‌ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---

If the variables are correlated, the points will fall along a line or curve. The

better the correlation, the tighter the points will hug the line.

Summary:

--- Content provided by FirstRanker.com ---





In bivariate analysis, the hypothesis of "association" and causality are tested. In

--- Content provided by​ FirstRanker.com ---


its simplest form, association simply refers to the extent to which it becomes

easier to know/predict a value for the Dependent Variable (DV) if we know a

--- Content provided by‌ FirstRanker.com ---

case's value on the Independent Variable (IV).



The two terms correlation and regression are distinct from each other and many

--- Content provided by⁠ FirstRanker.com ---


times are used interchangeably. Correlation is a statistical technique used for

measuring the relationship or interdependence of two or more variables.

--- Content provided by‌ FirstRanker.com ---

Regression analysis refers to the technique for deriving an equation that relates

the dependent variable to one or more variables. It is used to predict one variable

on the basis of another and hence helps in bringing out the causal relationship

--- Content provided by‍ FirstRanker.com ---


between two or more variables.



--- Content provided by​ FirstRanker.com ---

The Scatter Diagram is a tool for determining the potential correlation between

two different sets of variables, i.e., how one variable changes with the other

variable. This diagram simply plots pairs of corresponding data from two

--- Content provided by​ FirstRanker.com ---


variables.



--- Content provided by⁠ FirstRanker.com ---

Questions:



1) What is a chi-square test? What are the uses of the same?

--- Content provided by‌ FirstRanker.com ---


2) What is correlation analysis?

3) What is regression analysis?

--- Content provided by⁠ FirstRanker.com ---

4) What is the difference between correlation and regression analysis?

5) What are scatter diagrams? What do they depict?


--- Content provided by‌ FirstRanker.com ---


CHAPTER IV



--- Content provided by⁠ FirstRanker.com ---


Multivariate Analysis



--- Content provided by‍ FirstRanker.com ---

Objective:



The objective of this chapter is to understand:

--- Content provided by⁠ FirstRanker.com ---


The process of Multivariate analysis
Study about analysis of variation, Multiple Regression Analysis,

Discriminant Analysis, Conjoint Analysis, Factor Analysis, Cluster

--- Content provided by FirstRanker.com ---


Analysis and Multi-dimensional Scaling



--- Content provided by‌ FirstRanker.com ---

Introduction:



Multivariate analysis is the analysis of the simultaneous relationships among

--- Content provided by‌ FirstRanker.com ---


three or more phenomena. In Univariate analysis the focus is on the level

(average) and distribution (variance) of the phenomenon, in a bivariate analysis

--- Content provided by FirstRanker.com ---

the focus shifts to the degree of relationships (correlations or co variances)

between the phenomena. In a multivariate analysis, the focus shifts from paired

relationships to more complex simultaneous relationships among phenomena.

--- Content provided by​ FirstRanker.com ---




The various methods of Multivariate analysis are:

--- Content provided by FirstRanker.com ---



1. Analysis of Variance

2. Dependence Methods

--- Content provided by⁠ FirstRanker.com ---


Multiple Regression Analysis
Discriminant Analysis
Conjoint Analysis

--- Content provided by​ FirstRanker.com ---

3. Inter Dependence Methods


Factor Analysis
Cluster Analysis

--- Content provided by FirstRanker.com ---

Multi-dimensional Scaling



Analysis of Variance

--- Content provided by⁠ FirstRanker.com ---




This can be studied under ANOVA, ANCOVA, MANOVA and MANCOVA.

--- Content provided by FirstRanker.com ---



ANOVA: An ANOVA (Analysis of Variance), sometimes called an F test, is

closely related to the t test. The t test measures the difference between the means

--- Content provided by FirstRanker.com ---


of two groups whereas an ANOVA tests the difference between the means of

two or more groups.

--- Content provided by‍ FirstRanker.com ---



ANOVA can be a one-way ANOVA or a factorial ANOVA.


--- Content provided by‌ FirstRanker.com ---


One-way or single factor ANOVA, tests differences between groups that are

only classified on one independent variable. A factorial ANOVA can show

--- Content provided by​ FirstRanker.com ---

whether there are significant main effects of the independent variables and

whether there are significant interaction effects between independent variables

in a set of data. Interaction effects occur when the impact of one independent

--- Content provided by‍ FirstRanker.com ---


variable depends on the level of the second independent variable.



--- Content provided by⁠ FirstRanker.com ---

The advantage of using ANOVA rather than multiple t-tests is that it reduces the

probability of a type-I error. Making multiple comparisons increases the

likelihood of finding something by chance--making a type-I error.

--- Content provided by‍ FirstRanker.com ---





An F indicates that there is a significant difference between groups, not which

--- Content provided by FirstRanker.com ---


groups are significantly different from each other. This is one potential

drawback to an ANOVA, which is loss of specificity.

--- Content provided by​ FirstRanker.com ---



A factorial ANOVA can examine data that are classified on multiple

independent variables. More than two independent variables can be compared in

--- Content provided by FirstRanker.com ---


an ANOVA (e.g., three-way, four-way).



--- Content provided by‌ FirstRanker.com ---

ANCOVA: In ANCOVA, we can analyze both qualitative (class) and

quantitative (continuous) independent variables. The mixed procedure allows

the user to model both class and continuous variables. In ANOVA-type models,

--- Content provided by‌ FirstRanker.com ---


hypotheses about class or interactions among class variables are tests of means

or differences among means. In regression-type models, in which all factors

--- Content provided by‌ FirstRanker.com ---

are continuous variables (rather than categories), hypothesis tests are tests about

regression coefficients.


--- Content provided by‌ FirstRanker.com ---


As one might expect, the assumptions of ANCOVA combines both the

assumptions of regression and ANOVA. In addition, the tests of adjusted means

--- Content provided by​ FirstRanker.com ---

are based on the assumption that the class variable by covariate interaction is

negligible, that is the regression lines are parallel.


--- Content provided by FirstRanker.com ---


MANOVA: Multivariate analysis of variance (MANOVA) is simply an

ANOVA with several dependent variables. For example, we may conduct a

--- Content provided by‌ FirstRanker.com ---

study where we try two different textbooks, and we are interested in the students'

improvements in Physics and Chemistry. In that case, improvements in physics

and chemistry are the two dependent variables, and our hypothesis is that both

--- Content provided by​ FirstRanker.com ---


together are affected by the difference in textbooks. A multivariate analysis of

variance (MANOVA) could be used to test this hypothesis. Instead of a

--- Content provided by⁠ FirstRanker.com ---

univariate F value, we would obtain a multivariate F value (Wilks' lambda)

based on a comparison of the error variance/covariance matrix and the effect

variance/covariance matrix. The "covariance" here is included because the two

--- Content provided by​ FirstRanker.com ---


measures are probably correlated and we must take this correlation into account

when performing the significance test.

--- Content provided by‍ FirstRanker.com ---



MANOVA is useful in experimental situations where at least some of the

independent variables are manipulated. It has several advantages over ANOVA.

--- Content provided by‍ FirstRanker.com ---


1. By measuring several dependent variables in a single experiment, there

is a better chance of discovering which factor is truly important.

--- Content provided by‍ FirstRanker.com ---

2. It can protect against Type I errors that might occur if multiple

ANOVA`s were conducted independently. Additionally, it can reveal

differences not discovered by ANOVA tests.

--- Content provided by​ FirstRanker.com ---




However, there are several cautions as well. It is a substantially more

--- Content provided by FirstRanker.com ---

complicated design than ANOVA, and therefore there can be some ambiguity as

to which independent variable affects each dependent variable. Moreover, one

degree of freedom is lost for each dependent variable that is added. Finally, the

--- Content provided by‌ FirstRanker.com ---


dependent variables should be largely uncorrelated. If the dependent variables

are highly correlated, there is little advantage in including more than one in the

--- Content provided by‍ FirstRanker.com ---

test given the resultant loss in degrees of freedom.



Some of the assumptions made here are:

--- Content provided by⁠ FirstRanker.com ---




Normal Distribution: The dependent variable should be normally

--- Content provided by⁠ FirstRanker.com ---

distributed within groups. Overall, the F test is robust to non-normality

if it is caused by skewness rather than outliers. Tests for outliers should


--- Content provided by‌ FirstRanker.com ---

be run before performing a MANOVA, and outliers should be

transformed or removed.

Homogeneity of Variances: Homogeneity of variances assumes that the

--- Content provided by⁠ FirstRanker.com ---


dependent variables exhibit equal levels of variance across the range of

predictor variables.

--- Content provided by FirstRanker.com ---

Homogeneity of Variances and Covariance`s: In multivariate designs,

with multiple dependent measures, the homogeneity of variances

assumption described earlier also applies. However, since there are

--- Content provided by⁠ FirstRanker.com ---


multiple dependent variables, it is also required that their covariances are

homogeneous across the cells of the design. There are various specific

--- Content provided by‌ FirstRanker.com ---

tests of this assumption.



Two Special Cases arise in MANOVA:

--- Content provided by⁠ FirstRanker.com ---


Unequal sample sizes: As in ANOVA, when cells in a factorial

MANOVA have different sample sizes, the sum of squares for effect

--- Content provided by‌ FirstRanker.com ---

plus error does not equal the total sum of squares. This causes tests of

main effects and interactions to be correlated.

Within-subjects design: Problems arise if the researcher measures several

--- Content provided by‍ FirstRanker.com ---


different dependent variables on different occasions.



--- Content provided by​ FirstRanker.com ---

MANCOVA: MANCOVA is an extension of ANCOVA. It is simply a

MANOVA where the artificial direct variables are initially adjusted for

differences in one or more covariates. This can reduce error "noise" when error

--- Content provided by‌ FirstRanker.com ---


associated with the covariate is removed.



--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---


MULTIPLE REGRESSION ANALYSIS



--- Content provided by⁠ FirstRanker.com ---

Multiple regression is used to account for (predict) the variance in an interval

dependent, based on linear combinations of interval, dichotomous, or dummy

independent variables. Multiple regression can establish that a set of

--- Content provided by​ FirstRanker.com ---


independent variables explains a proportion of the variance in a dependent

variable at a significant level (through a significance test of R2), and can

--- Content provided by⁠ FirstRanker.com ---

establish the relative predictive importance of the independent variables.



The multiple regression equation takes the form

--- Content provided by​ FirstRanker.com ---




y = a + b1x1 + b2x2 + ... + bnxn

--- Content provided by⁠ FirstRanker.com ---



where y is the dependent variable which is to be predicted, x1, x2 and xn are the n
known variables on which the predictions are to be based and a, b1, b2, ....bn are

--- Content provided by‌ FirstRanker.com ---

parameters, the values of which are to be determined by the methods of least

squares.


--- Content provided by‌ FirstRanker.com ---


Associated with multiple regression is r2 (multiple correlation), which is the

percent of variance in the dependent variable explained collectively by all of the

--- Content provided by FirstRanker.com ---

independent variables.



(Y ? Y)2

--- Content provided by‌ FirstRanker.com ---


Y) ? (Y ? Y )2

)

--- Content provided by​ FirstRanker.com ---

r2

r =

i

--- Content provided by​ FirstRanker.com ---


i

c

--- Content provided by⁠ FirstRanker.com ---

=

(Y ? Y)2

Y)

--- Content provided by⁠ FirstRanker.com ---


i



--- Content provided by​ FirstRanker.com ---

where r2 is the co-efficient of determination, Yi is the value of ith item in Y
series, Y (bar) is the mean of the Y series and Yc is the computed value of the ith
item in Y series on the basis of the regression.


--- Content provided by‌ FirstRanker.com ---



Multiple regression shares all the assumptions of correlation: linearity of

relationships, the same level of relationship throughout the range of the

--- Content provided by FirstRanker.com ---


independent variable, interval or near-interval data, absence of outliers, and data

whose range is not truncated. In addition, it is important that the model being

--- Content provided by‍ FirstRanker.com ---

tested is correctly specified. The exclusion of important causal variables or the

inclusion of extraneous variables can change the interpretation of the importance

of the independent variables.

--- Content provided by‍ FirstRanker.com ---




Multiple regressions with dummy variables yield the same inferences as

--- Content provided by FirstRanker.com ---

multiple analysis of variance (MANOVA), to which it is statistically equivalent.

When the dependent variable is a dichotomy the assumptions of multiple

regressions cannot be met, discriminant analysis or logistic regression is used

--- Content provided by‌ FirstRanker.com ---


instead. Partial least squares regression is sometimes used to predict one set of

response variables from a set of independent variables

--- Content provided by⁠ FirstRanker.com ---



DISCRIMINANT ANALYSIS


--- Content provided by​ FirstRanker.com ---


Discriminant analysis is used to classify the sample into two or more categories.

Example: Consumers may be classified as heavy and light users; Sales people

--- Content provided by FirstRanker.com ---

can be classified as successful and unsuccessful and so on.

Discriminant function analysis is used to determine which variables discriminate

between two or more naturally occurring groups.

--- Content provided by⁠ FirstRanker.com ---


For example, a researcher may want to investigate which variables discriminate

between engineers who decide

--- Content provided by⁠ FirstRanker.com ---

(1) To seek employment in private companies,

(2) To take up government services, or

(3) To seek opportunities abroad.

--- Content provided by​ FirstRanker.com ---


For that purpose the researcher could collect data on numerous variables after

the graduation of the engineers. Discriminant Analysis could then be used to

--- Content provided by‍ FirstRanker.com ---

determine which variable(s) are the best predictors of the engineers` choice of

employment.

The objectives of two group discriminant analysis are to find a linear composite

--- Content provided by FirstRanker.com ---


of the predictor variable to help the analyst to separate the groups, establishing

procedures for assigning new individuals, testing for significant differences

--- Content provided by‌ FirstRanker.com ---

between the mean predictor variables and determining the variable which

accounts for the most intergroup differences.

This is commonly carried out with the help of a computer program.

--- Content provided by⁠ FirstRanker.com ---




CONJOINT ANALYSIS

--- Content provided by‍ FirstRanker.com ---



Conjoint analysis deals with the measurement of the combined effect of two or

more attributes that are important from the view of the consumer. The use of the

--- Content provided by‍ FirstRanker.com ---


conjoint analysis will be more appropriate in a situation where a company would

like to know the most desirable attribute for a new product or service.

--- Content provided by‍ FirstRanker.com ---



For example, a hotel would like to know whether choice of menu or prompt

service would attract a customer to visit them frequently.

--- Content provided by​ FirstRanker.com ---





For this, it will seek data from the consumer in the firm of response to identify

--- Content provided by​ FirstRanker.com ---


product attributes. The various options available for this are direct interview

with the customer or focus group interviews. All the attributes are weighed and

--- Content provided by‍ FirstRanker.com ---

compared.

The main steps involved in the application of conjoint analysis are


--- Content provided by⁠ FirstRanker.com ---


1. Determination of salient attributes: the attributes have to be selected

based on the marketers experience or through interviews. Only valuable

--- Content provided by⁠ FirstRanker.com ---

attributes need to be considered.

2. Assigning levels to the selected attributes: this can vary from most

preferred to the least preferred.

--- Content provided by⁠ FirstRanker.com ---


3. Fractional factorial design of experiments: during the comparison of

the profile of different products, it is essential to have a minimum

--- Content provided by​ FirstRanker.com ---

number of designs which provide us all the information required. This

will ensure easy management of the design.

4. Physical design of the stimuli: a prototype or a picture of the concept

--- Content provided by FirstRanker.com ---


may be given to the consumer or customer to get a realistic picture.

5. Data collection: The customers are asked to rank all the alternatives

--- Content provided by⁠ FirstRanker.com ---

using a rating scale. This will ensure ease of data collection and analysis.

6. Determination of part-worth utilities: Regression methods,

mathematical programming methods, econometric methods may be used

--- Content provided by FirstRanker.com ---


for the part-worth utility values.



--- Content provided by‌ FirstRanker.com ---

The applications of conjoint analysis are

It can be used for optimum product design based on the attributes

considered. Simulations can be created to represent competitors`

--- Content provided by​ FirstRanker.com ---


action or a fresh scenario.


Consumers can be segmented based on their sensitivity to

--- Content provided by⁠ FirstRanker.com ---


product attributes.

It may help a manager to conduct SWOT analysis of the brand as

--- Content provided by⁠ FirstRanker.com ---

the part-worth utility speaks about the relative brand strength.



There are certain limitations of conjoint analysis. It may not be perfect and

--- Content provided by FirstRanker.com ---


convincing and may fail to capture utility functions and decision roles.



--- Content provided by‌ FirstRanker.com ---



FACTOR ANALYSIS


--- Content provided by‍ FirstRanker.com ---


Factor analysis is a name given to a class of techniques whose purpose is data

reduction and summarization. The data from market research are vast and factor

--- Content provided by FirstRanker.com ---

analysis helps in reducing the number of variables. Factor analysis is an

explorative technique.


--- Content provided by⁠ FirstRanker.com ---


Factor analysis was invented nearly 100 years ago by psychologist Charles

Spearman, who hypothesized that the enormous variety of tests of mental

--- Content provided by⁠ FirstRanker.com ---

ability--measures of mathematical skill, vocabulary, other verbal skills, artistic

skills, logical reasoning ability, etc.--could all be explained by one underlying

"factor" of general intelligence that he called g. He hypothesized that if g could

--- Content provided by​ FirstRanker.com ---


be measured and you could select a subpopulation of people with the same score

on g, in that subpopulation you would find no correlations among any tests of

--- Content provided by​ FirstRanker.com ---

mental ability. In other words, he hypothesized that g was the only factor

common to all those measures.


--- Content provided by⁠ FirstRanker.com ---



The objectives of factor analysis are simplifying the data by reducing a large

number of variables to a set of a small number of variables and analyzing the

--- Content provided by⁠ FirstRanker.com ---


interdependence of relationship among a total set of variables.



--- Content provided by​ FirstRanker.com ---

Factor analysis can be used in several ways as given below:

1. It brings out the hidden dimensions relevant to a researcher among

product preferences.

--- Content provided by FirstRanker.com ---


2. Helps to find out relationships among observed values.

3. Used when the data is large and has to be simplified and condensed.

--- Content provided by⁠ FirstRanker.com ---



The limitations of factor analysis are:

It is a complicated tool and should be used if the researcher has a

--- Content provided by⁠ FirstRanker.com ---


good understanding of the technique.

The reliability of the results is some times questionable.
It suitability depends on the judgment of the researcher.

--- Content provided by‌ FirstRanker.com ---




Factor analysis is used in the case of exploratory research and has to be used

--- Content provided by FirstRanker.com ---

were the concepts are well formulated and tested.



CLUSTER ANALYSIS

--- Content provided by‍ FirstRanker.com ---




Cluster analysis is a technique used to segment a market. It is used to classify a

--- Content provided by‌ FirstRanker.com ---

person or object into a small number or mutually exclusive and exhaustive

groups. Its object is to sort cases (people, things, events, etc) into groups, or

clusters, so that the degree of association is strong between members of the same

--- Content provided by​ FirstRanker.com ---


cluster and weak between members of different clusters. Each cluster thus

describes, in terms of the data collected, the class to which its members belong;

--- Content provided by⁠ FirstRanker.com ---


and this description may be abstracted through use from the particular to the

general class or type.

--- Content provided by⁠ FirstRanker.com ---



CA lacks an underlying body of statistical theory and is heuristic in nature.

Cluster analysis requires decisions to be made by the user relating to the

--- Content provided by​ FirstRanker.com ---


calculation of clusters, decisions which have a strong influence on the results of

the classification. CA is useful to classify groups or objects and is more

--- Content provided by FirstRanker.com ---

objective than subjective.

Cluster analysis, like factor analysis and multi dimensional scaling, is an

interdependence technique: it makes no distinction between dependent and

--- Content provided by‌ FirstRanker.com ---


independent variables. The entire set of interdependent relationships is

examined. It is similar to multi dimensional scaling in that both examine inter-

--- Content provided by FirstRanker.com ---

object similarity by examining the complete set of interdependent relationships.

The difference is that multi dimensional scaling identifies underlying

dimensions, while cluster analysis identifies clusters. Cluster analysis is the

--- Content provided by‍ FirstRanker.com ---


obverse of factor analysis. Whereas factor analysis reduces the number of

variables by grouping them into a smaller set of factors, cluster analysis reduces

--- Content provided by​ FirstRanker.com ---

the number of observations or cases by grouping them into a smaller set of

clusters.


--- Content provided by⁠ FirstRanker.com ---


In marketing, cluster analysis is used for:

Segmenting the market and determining target markets
Product positioning and New Product Development

--- Content provided by‍ FirstRanker.com ---

Selecting test markets



Example: A supermarket might gather data on all of their existing customers

--- Content provided by​ FirstRanker.com ---


and survey them regarding their buying criteria relative to the product line. They

could then use cluster analysis to group customers with similar buying patterns

--- Content provided by​ FirstRanker.com ---

together. This type of cluster analysis, also known as market segmentation, is

performed at increasing rates, due to the advent of high-speed computers and the

ready availability of demographic data. Based on the broader descriptions of

--- Content provided by‌ FirstRanker.com ---


individuals within each cluster, the retail managers could make decisions that

would be appropriate for the individuals within.

--- Content provided by⁠ FirstRanker.com ---



Clusters for this example might include:


--- Content provided by FirstRanker.com ---


Price-sensitive shoppers
Indifferent shoppers
Quality-focused shoppers
High-end status shoppers

--- Content provided by​ FirstRanker.com ---

Monthly shopper



Clustering methods may be top down and employ logical division, or bottom up

--- Content provided by​ FirstRanker.com ---


and undertake aggregation. Aggregation procedures which are based upon

combining cases through assessment of similarities are the most common and

--- Content provided by‌ FirstRanker.com ---

popular will be the focus of this section.



Care should be taken that groups (classes) are meaningful in some fashion and

--- Content provided by FirstRanker.com ---


are not arbitrary or artificial. To do so the clustering techniques attempt to have

minimal internal variation as compared to maximal variation between groups.

--- Content provided by⁠ FirstRanker.com ---

Homogeneous and distinct groups are delineated based upon assessment of

distances or an F-test.


--- Content provided by​ FirstRanker.com ---


Steps in Cluster Analysis:



--- Content provided by‍ FirstRanker.com ---


The two key steps within cluster analysis are the measurement of distances

between objects and to group the objects based upon the resultant distances

--- Content provided by⁠ FirstRanker.com ---

(linkages).



The distances provide for a measure of similarity between objects and may be

--- Content provided by⁠ FirstRanker.com ---


measured in a variety of ways, such as Euclidean and Manhattan metric

distance. The criteria used to then link (group) the variables may also be

--- Content provided by FirstRanker.com ---

undertaken in a variety of manners, as a result significant variation in results

may be seen.

Linkages are based upon how the association between groups is measured. For

--- Content provided by FirstRanker.com ---


example, simple linkage or nearest neighbor distance, measures the distance to

the nearest object in a group while furthest neighbor linkage or complete

--- Content provided by​ FirstRanker.com ---

linkage, measures the distance between furthest objects. These linkages are both

based upon single data values within groups, whereas average between group

linkages is based upon the distance from all objects in a group. Centroid linkage

--- Content provided by FirstRanker.com ---


has a new value, representing the group centroid, which is compared to the

ungrouped point to weigh inclusion.

--- Content provided by‌ FirstRanker.com ---



Ward's method is variance based with the groups variance assessed to enable

clustering. The group which sees the smallest increase in variance with the

--- Content provided by​ FirstRanker.com ---


iterative inclusion of a case will receive the case. Ward's is a popular default

linkage which produces compact groups of well distributed size. Standardization

--- Content provided by FirstRanker.com ---

of variables is undertaken to enable the comparison of variables to minimize the

bias in weighting which may result from differing measurement scales and

ranges. Z score format accounts for differences between mean values and

--- Content provided by FirstRanker.com ---


reduces the standard deviation when variables have multivariate normality



--- Content provided by FirstRanker.com ---

Choosing number of groups:



The ideal number of groups to establish may be assessed graphically or

--- Content provided by​ FirstRanker.com ---


numerically. Graphically the number of groups may be assessed with an icicle

plot or dendrogram. The dendrogram bisected at a point which will divide the

--- Content provided by​ FirstRanker.com ---

cases into a cluster based upon groupings up to the point where the bisection

occurred. Numerically the number of cases may be assessed on the

agglomeration schedule, by counting up from the bottom to where a significant

--- Content provided by⁠ FirstRanker.com ---


break in slope (numbers) occurs.



--- Content provided by⁠ FirstRanker.com ---





The optimal number of groups may be assessed based upon knowledge of the

--- Content provided by FirstRanker.com ---


data set. Discriminant analysis may also be employed to assess optimality and


efficiency of computed groups, by imputing the cluster analysis derived classes

--- Content provided by⁠ FirstRanker.com ---


for analysis with the original data.



--- Content provided by‍ FirstRanker.com ---

Like the other techniques, cluster analysis presents the problem of how many

factors, or dimensions or clusters to keep. One rule followed here is to choose a

place where the cluster structure remains stable for a long distance. Some other

--- Content provided by​ FirstRanker.com ---


possibilities are to look for cluster groupings that agree with existing or expected

structures, or to replicate the analysis on subsets of the data to see if the

--- Content provided by‍ FirstRanker.com ---

structures emerge consistently.




--- Content provided by‌ FirstRanker.com ---


MULTI-DIMENSIONAL SCALING



--- Content provided by‌ FirstRanker.com ---

Multi-dimensional scaling (MDS) or perceptual map or positioning map is used

for measuring human perception and preferences. It is spatial representation of

relationships. It helps in the identification of attributes and the positioning of

--- Content provided by‍ FirstRanker.com ---


different products or brands on the basis of these attributes.

MDS is of two types, metric MDS and non metric MDS.

--- Content provided by FirstRanker.com ---



Given below is an example of a perceptual map. AC represents the x-axis and

BD represents the y-axis. The value of the variable may be low to high from one

--- Content provided by‍ FirstRanker.com ---


end of the axis to the other.



--- Content provided by FirstRanker.com ---


C

D

--- Content provided by​ FirstRanker.com ---

B

A


--- Content provided by​ FirstRanker.com ---




Two approaches can be used for analyzing multi dimensional data. It can be

--- Content provided by​ FirstRanker.com ---

done by measuring the attributes or distance between objects.



For MDS, a set of number called proximities and a computer based algorithms

--- Content provided by‍ FirstRanker.com ---


must be available.

The applications of MDS in marketing are in market segmentation, vendor

--- Content provided by FirstRanker.com ---

evaluation, attitude scaling, advertisement evaluation, product repositioning,

new product development and test marketing. Thus MDS measures the

psychological distance or the dis-similarities to evaluate the external

--- Content provided by‍ FirstRanker.com ---


environment.

The limitations of MDS are

--- Content provided by FirstRanker.com ---

Concepts of similarity and preferences may differ
The selection of attributes are subjective
It is at time difficult to interpret the results
Different computer programmes may produce different results

--- Content provided by⁠ FirstRanker.com ---




Summary

--- Content provided by‌ FirstRanker.com ---

This chapter deals with the different methods used in multivariate analysis and

briefly describes their application. The methods are chosen based on the data

and requirements of analysis.

--- Content provided by‌ FirstRanker.com ---




Questions:

--- Content provided by‍ FirstRanker.com ---

1. What is multivariate analysis? Explain.

2. Briefly explain the methods of multivariate analysis.

3. Explain variance of analysis. Write a note on the different types.

--- Content provided by⁠ FirstRanker.com ---


4. What is multiple regression analysis?

5. What is discriminant analysis? How is it useful in Marketing?

--- Content provided by​ FirstRanker.com ---

6. What are the steps involved in the application of conjoint analysis?

7. What are the limitations and uses of factor analysis?

8. What is cluster analysis? What are the steps involved in cluster

--- Content provided by​ FirstRanker.com ---


analysis?

9. What is Multi-dimensional scaling? Where is it used?

--- Content provided by FirstRanker.com ---

10. How do you choose a method for analysis?

CHAPTER V


--- Content provided by‌ FirstRanker.com ---


REPORT WRITNG



--- Content provided by‌ FirstRanker.com ---

Objective:



The objective of this chapter is to understand:

--- Content provided by⁠ FirstRanker.com ---




Importance of report writing
Types of reports

--- Content provided by⁠ FirstRanker.com ---

Considerations for oral and written reports


Steps in the preparation of the report
Presentation of data and feedback

--- Content provided by‌ FirstRanker.com ---




Report Writing

--- Content provided by⁠ FirstRanker.com ---



It is not sufficient if the market researcher has collected information on the

research problem, he also has to interpret the data and draw specific conclusions

--- Content provided by​ FirstRanker.com ---


from it. The results of marketing research must be effectively communicated to

management. This report has to be clear and concise.

--- Content provided by⁠ FirstRanker.com ---



Types of Report:


--- Content provided by⁠ FirstRanker.com ---


Reports can be broadly classified into two types: oral and written.



--- Content provided by‍ FirstRanker.com ---

Presenting the results of a marketing research study to management generally

involves a formal written report as well as an oral presentation. The report and

presentation are extremely important. This is because:

--- Content provided by‍ FirstRanker.com ---


1. The results of marketing research are often intangible (there is very little

physical evidence of the resources, such as time and effort, that went into

--- Content provided by FirstRanker.com ---

the project); the written report is usually the only documentation of the

project.

2. The written report and the oral presentation are the only aspect of the

--- Content provided by⁠ FirstRanker.com ---


study that marketing executives are exposed to, and consequently the

overall evaluation of the research project rests on how well this

--- Content provided by‌ FirstRanker.com ---

information is communicated. They might not have been part of the

marketing research study and hence will not know what information was

collected.

--- Content provided by‌ FirstRanker.com ---



3. Since the written research report and oral presentation are typically the

responsibility of the marketing research supplier, the communication

--- Content provided by FirstRanker.com ---


effectiveness and usefulness of the information provided plays a crucial

role in determining the choice of the particular marketing research

--- Content provided by⁠ FirstRanker.com ---

supplier for the future.



Differences between oral and written reports:

--- Content provided by​ FirstRanker.com ---




An oral report is any presentation that is verbally done to the management.

--- Content provided by‌ FirstRanker.com ---

Written reports are documentation of the research findings.



There are three major differences between oral and written reports.

--- Content provided by FirstRanker.com ---




1. Oral reports are difficult to interpret as they lack visual advantage.

--- Content provided by⁠ FirstRanker.com ---

Charts, diagrams or pictures cannot be used to stress on important points.

They have to rely only on pauses and volume emphasis.

2. The pace of the presentation cannot be controlled and regulated by the

--- Content provided by FirstRanker.com ---


audience who is being presented with the oral report. In a written report,

the reader can clarify a certain point by reading it two or more times, if

--- Content provided by​ FirstRanker.com ---

needed slowly and carefully.

3. A researcher will write the report very precisely and with more accuracy

since he is aware that a written report is bound to receive considerable

--- Content provided by⁠ FirstRanker.com ---


attention and scrutiny from the readers. In contrast, an oral report will

not be so precise nor will the researcher give as much time in its

--- Content provided by‌ FirstRanker.com ---

presentation since it cannot be subjected to the same degree of scrutiny

as a written report.


--- Content provided by‌ FirstRanker.com ---


Considerations for Oral Reporting



--- Content provided by⁠ FirstRanker.com ---

A researcher has to consider the following when he has been asked to make an

oral presentation:


--- Content provided by⁠ FirstRanker.com ---


Consider the audience to whom the report has to be presented and

prepare the same so as to incorporate the technical requirements.

--- Content provided by​ FirstRanker.com ---

It should be properly planned. The researcher has to rehearse what he is

going to say or recommend. He has to collect and organize the data in a

logical manner.

--- Content provided by​ FirstRanker.com ---


Suitability of the language is another point worth considering. The

reporting has to be simple, concise and clear.

--- Content provided by‍ FirstRanker.com ---

Visual aids like charts, graphs and handouts can be used judiciously if

required to create a better impact. However this also needs to be used

sparingly as it might disturb the proceedings.

--- Content provided by‍ FirstRanker.com ---






--- Content provided by FirstRanker.com ---





Consideration for Written Reporting

--- Content provided by FirstRanker.com ---




Every person has a different style of writing. There is not really one right style

--- Content provided by‍ FirstRanker.com ---

for a report, but there are some basic principles for writing a research report

clearly.


--- Content provided by⁠ FirstRanker.com ---


Types of Report:

There are many classifications available for reports. Some of them are listed

--- Content provided by‍ FirstRanker.com ---

below:



Sl. No.

--- Content provided by‍ FirstRanker.com ---


Classification

Types

--- Content provided by‌ FirstRanker.com ---

Daily, Weekly, Fortnightly, Monthly or

1 Time interval

Annual

--- Content provided by​ FirstRanker.com ---


2 Functional Basis

Informational, Examinational and Analytical
Economics, Finance, Industry, and other

--- Content provided by​ FirstRanker.com ---


3 Subject Matter

subjects of interest

--- Content provided by‍ FirstRanker.com ---

4 Physical-form

Short-form and Long-form

Relationship between the reader

--- Content provided by⁠ FirstRanker.com ---


Administrative, Professional and

5 and the writer

--- Content provided by‍ FirstRanker.com ---

Independent

6 Employment status of authors

Private and Public reports

--- Content provided by FirstRanker.com ---


7 Formality

Formal and Informal

--- Content provided by⁠ FirstRanker.com ---



None of these are mutually exclusive. A report may be a combination of some of

the above.

--- Content provided by⁠ FirstRanker.com ---




Preparation of the Report

--- Content provided by‌ FirstRanker.com ---



Preparing a research report is just not writing alone, but involves other activities

besides writing. In fact, writing is actually the last step in the preparation

--- Content provided by FirstRanker.com ---


process. Before writing can take place, the results of the research project must

be fully understood and thought must be given to what the report will say. The

--- Content provided by‌ FirstRanker.com ---

objectives of the research should be matched with the results and the report has

to be written.


--- Content provided by‍ FirstRanker.com ---


Thus, preparing a research report involves three steps:

1. Understanding: Understand the objective of the research and then

--- Content provided by‌ FirstRanker.com ---

provide the solution.

2. Organizing: Organize your thoughts and findings and build a logical

flow.

--- Content provided by​ FirstRanker.com ---


3. Writing: Now, draft the outline of your report and then write the same.



--- Content provided by​ FirstRanker.com ---


The general guidelines that should be followed for any report or research paper

are as follows:

--- Content provided by⁠ FirstRanker.com ---



Consider the audience: The information resulting from the study is

going to be used by the marketing managers, who will use the results to

--- Content provided by‍ FirstRanker.com ---


make decisions. Thus, the report has to be understood by them; the report

should not be too technical and not too much jargon should be used.

--- Content provided by⁠ FirstRanker.com ---



This is a particular difficulty when reporting the results of statistical

analysis where there is a high probability that few of the target audience

--- Content provided by​ FirstRanker.com ---


have a grasp of statistical concepts. Hence, this needs to be translated

into simple language.

--- Content provided by​ FirstRanker.com ---



Be concise, but precise: Many a time, the researcher in order to convey

his effort, tends to overcrowd the report with data. This leads to loss of

--- Content provided by‍ FirstRanker.com ---


focus. On the one hand, a written report should be complete in the sense

that it stands by itself and that no additional clarification is needed. On

--- Content provided by FirstRanker.com ---

the other hand, the report must be concise and must focus on the critical

elements of the project and must exclude unimportant issues. Hence, a

research report has to be concise and precise.

--- Content provided by‌ FirstRanker.com ---




Understand the results and draw conclusions: The managers who read

--- Content provided by⁠ FirstRanker.com ---

the report are expecting to see interpretive conclusions in the report. The

researcher must therefore understand the results and be able to interpret

these. He should analyze the results and present them to the managers.

--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---

Research Report Format



The following outline is the suggested format for writing the research report:

--- Content provided by‌ FirstRanker.com ---




1. Title page

--- Content provided by‌ FirstRanker.com ---

2. Letter of Authorization

3. Summary of findings

4. Table of contents

--- Content provided by‍ FirstRanker.com ---


o List of tables

o List of figures

--- Content provided by‍ FirstRanker.com ---

5. Introduction

o Background to the research problem

o Objectives

--- Content provided by‍ FirstRanker.com ---


o Hypotheses

6. Methodology

--- Content provided by FirstRanker.com ---

o Data collection

o Sample and sampling method

o Statistical or qualitative methods used for data analysis

--- Content provided by‌ FirstRanker.com ---


o Sample description

7. Findings

--- Content provided by​ FirstRanker.com ---

8. Limitations

9. Results, interpretation and conclusions.

10. Recommendations

--- Content provided by‌ FirstRanker.com ---


11. Appendices

12. Bibliography

--- Content provided by FirstRanker.com ---



The title page indicates the topic on which the report has been prepared, the date

of submission, Prepared by and Prepared for details.

--- Content provided by​ FirstRanker.com ---




The letter of authorization is provided to facilitate the research process.

--- Content provided by FirstRanker.com ---



The summary of findings is perhaps the most important component of the

written report, since many of the management team who are to receive a copy of

--- Content provided by⁠ FirstRanker.com ---


the report will only read this section. The summary of findings is usually put

right after the title page, or is bound separately and presented together with the

--- Content provided by FirstRanker.com ---

report.



The table of contents guides the reader as to what it contains and helps him to

--- Content provided by‍ FirstRanker.com ---


navigate the document. A separate table has to be provided for the charts and

graphs if they are part of the research report.

--- Content provided by‍ FirstRanker.com ---



The introduction should describe the background of the study and the details of

the research problem. Following that, automatically the broad aim of the

--- Content provided by‌ FirstRanker.com ---


research can be specified, which is then translated into a number of specific

objectives. Furthermore, the hypotheses that are to be tested in the research are

--- Content provided by‍ FirstRanker.com ---

stated in this section.



In the methodology chapter the sampling methods and procedures are described,

--- Content provided by‍ FirstRanker.com ---


as well as the different statistical methods that are used for data analysis.

Finally, the sample is described, giving the overall statistics, usually consisting

--- Content provided by⁠ FirstRanker.com ---

of frequency counts for the various sample characteristics.



Once the sample has been described, the main findings are to be presented in

--- Content provided by⁠ FirstRanker.com ---


such a way that all objectives of the study are achieved and the hypotheses are

tested. As mentioned before, it is essential that the main findings are well

--- Content provided by⁠ FirstRanker.com ---

interpreted and conclusions are drawn wherever possible.



The limitations or the caveats of the study should also be mentioned so that the

--- Content provided by FirstRanker.com ---


manager understands the pitfalls in the research process and he can make

suitable assumptions for his decision making.

--- Content provided by FirstRanker.com ---



Recommendations are required if the manager has specifically asked the agency

to suggest certain measures at the end of the research.

--- Content provided by​ FirstRanker.com ---




Appendix contains supporting materials for the report which cannot be given in

--- Content provided by​ FirstRanker.com ---

the body of the text. The bibliography details provide the details of the sources

which were referenced for the preparation of the report. The index shows the

various topics and the relevant page numbers in the report in an alphabetical

--- Content provided by‍ FirstRanker.com ---


order.



--- Content provided by⁠ FirstRanker.com ---

Data presentation



Easy-to-understand tables and graphics will greatly enhance the readability of

--- Content provided by⁠ FirstRanker.com ---


the written research report. As a general rule, all tables and figures should

contain:

--- Content provided by⁠ FirstRanker.com ---



1. Identification number corresponding to the list of tables and the list of

figures

--- Content provided by⁠ FirstRanker.com ---


2. A title that conveys the content of the table or figure, also corresponding

to the list of tables and the list of figures, and

--- Content provided by‌ FirstRanker.com ---

3. Appropriate column labels and row labels for tables, and figure legends

defining specific elements in the figure.


--- Content provided by⁠ FirstRanker.com ---


There are a number of ways to produce tables and figures. When typing a report

on a typewriter or word-processor, it is sometimes easiest to type a table out by

--- Content provided by FirstRanker.com ---

hand. However, when complicated tables have to be produced, it is advisable to

use spreadsheet software like Lotus 123 or Excel.


--- Content provided by FirstRanker.com ---


Feedback on the Report



--- Content provided by‌ FirstRanker.com ---

A feedback should be sought from the manger to whom the report has been

submitted. This will help the researcher to understand the drawbacks of his

report and improve on the same. Feedback is generally not given and it has to be

--- Content provided by​ FirstRanker.com ---


sought. This will help the researcher to improve his services during the future

projects.

--- Content provided by⁠ FirstRanker.com ---



Summary:


--- Content provided by‍ FirstRanker.com ---


It is not sufficient if the market researcher has collected information on the

research problem, he also has to interpret the data and draw specific conclusions

--- Content provided by⁠ FirstRanker.com ---

from it.



Presenting the results of a marketing research study to management generally

--- Content provided by‌ FirstRanker.com ---


involves a formal written report as well as an oral presentation. The report and

presentation are extremely important.

--- Content provided by‍ FirstRanker.com ---



Preparing a research report involves three steps:

1. Understanding: Understand the objective of the research and then

--- Content provided by⁠ FirstRanker.com ---


provide the solution.

2. Organizing: Organize your thoughts and findings and build a logical

--- Content provided by‍ FirstRanker.com ---

flow.

3. Writing: Now, draft the outline of your report and then write the same.


--- Content provided by‍ FirstRanker.com ---


The following outline is the suggested format for writing the research report:



--- Content provided by FirstRanker.com ---

1. Title page

2. Letter of Authorization

3. Summary of findings

--- Content provided by FirstRanker.com ---


4. Table of contents

o List of tables

--- Content provided by FirstRanker.com ---

o List of figures

5. Introduction

o Background to the research problem

--- Content provided by‍ FirstRanker.com ---


o Objectives

o Hypotheses

--- Content provided by FirstRanker.com ---

6. Methodology

o Data collection

o Sample and sampling method

--- Content provided by‌ FirstRanker.com ---


o Statistical or qualitative methods used for data analysis

o Sample description

--- Content provided by‍ FirstRanker.com ---

7. Findings

8. Limitations

9. Results, interpretation and conclusions.

--- Content provided by‌ FirstRanker.com ---


10. Recommendations

11. Appendices

--- Content provided by‍ FirstRanker.com ---

12. Bibliography



Questions:

--- Content provided by​ FirstRanker.com ---




1. List out the differences between an oral and a written report.

--- Content provided by‌ FirstRanker.com ---

2. When oral reports preferred and what are the considerations for it?


3. What are the points to be remembered which making a written report?

--- Content provided by FirstRanker.com ---

4. How are reports classified? Explain.

5. What is an outline? How is it useful for the preparation of a report?

6. Describe the various steps involved in writing a report.

--- Content provided by​ FirstRanker.com ---


7. Is feedback important for a report? Why?

8. How important do you think are writing skills and language important in

--- Content provided by‍ FirstRanker.com ---

presenting the research findings?

9. Imagine that you are presenting a report to a head of an education

institution. Write a report on the current educational system and how

--- Content provided by​ FirstRanker.com ---


your institute can make a difference.

10. Writing a report is different from conducting a research. Explain.

--- Content provided by​ FirstRanker.com ---






--- Content provided by⁠ FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---



CHAPTER VI


--- Content provided by FirstRanker.com ---


PARETO ANALYSIS



--- Content provided by​ FirstRanker.com ---

Objective:



The objective of this chapter is to understand:

--- Content provided by‌ FirstRanker.com ---




The meaning of Pareto analysis
Defining the Pareto effect

--- Content provided by​ FirstRanker.com ---

Steps involved in creating a Pareto chart


Importance of Pareto analysis

--- Content provided by‌ FirstRanker.com ---



Introduction:


--- Content provided by⁠ FirstRanker.com ---


Pareto analysis is a very simple technique that helps a manager to choose the

most effective changes to make. It is represented as a bar graph used to arrange

--- Content provided by‌ FirstRanker.com ---

information in such a way that priorities for process improvement can be

established. Pareto charts are constructed to provide a before-and-after

comparison of the effect of control or quality improvement measures.

--- Content provided by⁠ FirstRanker.com ---




The 80-20 theory was first developed in 1906, by an Italian economist, Vilfredo

--- Content provided by‍ FirstRanker.com ---

Pareto, who observed an unequal distribution of wealth and power in a relatively

small proportion of the total population. Joseph M. Juran adapted Pareto's

economic observations to business applications.

--- Content provided by‍ FirstRanker.com ---




Pareto Analysis is also used in inventory management through an approach

--- Content provided by FirstRanker.com ---

called "ABC Classification". The ABC classification system works by grouping

items by annual sales volume. This helps identify the small number of items that

will account for most of the sales volume and that are the most important ones to

--- Content provided by⁠ FirstRanker.com ---


control for effective inventory management. Thus it helps in effective inventory

management.

--- Content provided by​ FirstRanker.com ---



The Pareto effect


--- Content provided by‌ FirstRanker.com ---


In practically every industrial country a small proportion of all the factories

employ a disproportionate number of factory operatives. In some countries 15

--- Content provided by‍ FirstRanker.com ---

percent of the firms employ 70 percent of the people. This same state of affairs


is repeated time after time. In retailing for example, one usually finds that up to

--- Content provided by‍ FirstRanker.com ---

80 percent of the turnover is accounted for by 20 percent of the lines.



This effect, known as the 80 : 20 rule, can be observed in action so often that it

--- Content provided by⁠ FirstRanker.com ---


seems to be almost a universal truth. As several economists have pointed out, at

the turn of the century the bulk of the country`s wealth was in the hands of a

--- Content provided by‌ FirstRanker.com ---

small number of people.



This fact gave rise to the Pareto effect or Pareto`s law: a small proportion of

--- Content provided by​ FirstRanker.com ---


causes produce a large proportion of results. Thus frequently a vital few causes

may need special attention wile the trivial many may warrant very little. It is this

--- Content provided by‍ FirstRanker.com ---

phrase that is most commonly used in talking about the Pareto effect ? the vital

few and the trivial many`. A vital few customers may account for a very large

percentage of total sales. A vital few taxes produce the bulk of total revenue. A

--- Content provided by‌ FirstRanker.com ---


vital few improvements can produce the bulk of the results.



--- Content provided by⁠ FirstRanker.com ---

The Pareto effect is named after Vilfredo Pareto, an economist and sociologist

who lived from 1848 to 1923. Originally trained as an engineer he was a one

time managing director of a group of coalmines. Later he took the chair of

--- Content provided by‍ FirstRanker.com ---


economics at Lausanne University, ultimately becoming a recluse. Mussolini

made him a senator in 1922 but by his death in 1923 he was already at odds with

--- Content provided by⁠ FirstRanker.com ---

the regime. Pareto was an elitist believing that the concept of the vital few and

the trivial many extended to human beings.


--- Content provided by FirstRanker.com ---


This method stems in the first place from Pareto`s suggestion of a curve of the

distribution of wealth in a book of 1896. Whatever the source, the phrase of the

--- Content provided by​ FirstRanker.com ---

vital few and the trivial many` deserves a place in every manager`s thinking. It


is itself one of the most vital concepts in modern management. The results of

--- Content provided by​ FirstRanker.com ---

thinking along Pareto lines are immense.



For example, there may be a lot of customer complaints, a lot of shop floor

--- Content provided by FirstRanker.com ---


accidents, a high percentage of rejects, and a sudden increase in costs etc. The

first stage is to carry out a Pareto analysis. This is nothing more than a list of

--- Content provided by FirstRanker.com ---

causes in descending order of their frequency or occurrence. This list

automatically reveals the vital few at the top of the list, gradually tailing off into

the trivial many at the bottom of the list. Management`s task is now clear and

--- Content provided by​ FirstRanker.com ---


unavoidable: effort must be expended on those vital few at the head of the list

first. This is because nothing of importance can take place unless it affects the

--- Content provided by​ FirstRanker.com ---

vital few. Thus management`s attention is unavoidably focused where it will do

most good.


--- Content provided by‍ FirstRanker.com ---


Another example is stock control. You frequently find an elaborate procedure

for stock control with considerable paperwork flow. This is usually because the

--- Content provided by‍ FirstRanker.com ---

systems and procedures are geared to the most costly or fast-moving items. As a

result trivial parts may cost a firm more in paperwork than they cost to purchase

or to produce. An answer is to split the stock into three types, usually called A,

--- Content provided by‌ FirstRanker.com ---


B and C. Grade A items are the top 10 percent or so in money terms while grade

C are the bottom 50-75 percent. Grade B are the items in between. It is often

--- Content provided by​ FirstRanker.com ---

well worthwhile treating these three types of stock in a different way leading to

considerable savings in money tied up in stock.


--- Content provided by‍ FirstRanker.com ---


Production control can use the same principle by identifying these vital few

processes, which control the manufacture, and then building the planning around

--- Content provided by⁠ FirstRanker.com ---

these key processes. In quality control concentrating in particular on the most


troublesome causes follows the principle. In management control, the principle

--- Content provided by FirstRanker.com ---

is used by top management looking continually at certain key figures.



Thus it is clear that the Pareto concept ? the vital few and the trivial many` ? is

--- Content provided by‌ FirstRanker.com ---


of utmost importance to management.



--- Content provided by⁠ FirstRanker.com ---

Pareto Charts:



Pareto charts provide a tool for visualizing the Pareto principle, which states that

--- Content provided by​ FirstRanker.com ---


a small set of problems (the "vital few") affecting a common outcome tend to

occur much more frequently than the remainder (the "useful many"). A Pareto

--- Content provided by​ FirstRanker.com ---

chart can be used to decide which subset of problems should be solved first, or

which problems deserve the most attention.


--- Content provided by FirstRanker.com ---


The Pareto Chart is used to illustrate occurrences of problems or defects in a

descending order. It is used for making decisions at critical points in different

--- Content provided by‌ FirstRanker.com ---

processes. This means that it can be used both during the development process

as well as when products are in use, e.g. customer complaints.


--- Content provided by⁠ FirstRanker.com ---




How to create a Pareto Chart:

--- Content provided by⁠ FirstRanker.com ---



First step is to list all elements of interest
Use the same unit of measurement and measure each of the elements.
Order the elements according to their measure

--- Content provided by​ FirstRanker.com ---

Calculate the percentage for each element out of the total measurement
Accumulate the percentage from top to bottom to equal 100 %


Create a bar and line graph, line representing cumulative percentage

--- Content provided by FirstRanker.com ---

Work on the most important element first



Advantages of Pareto Charts:

--- Content provided by‌ FirstRanker.com ---




Pareto charts are a key improvement tool because they help us identify patterns

--- Content provided by FirstRanker.com ---

and potential causes of a problem. Several Pareto charts can be created out of

the same set of data. This will help a manager to quickly scan a number of

factors that might contribute to a problem and focus on those with the greatest

--- Content provided by‌ FirstRanker.com ---


potential payback for his efforts



--- Content provided by FirstRanker.com ---

It is difficult to choose which issue to work on first when faced with a range of

issues. To resolve this dilemma, the most useful thing to do is to apply Pareto's

rule. This rule says - "eighty percent of your troubles will come from 20 per cent

--- Content provided by⁠ FirstRanker.com ---


of your problems". In other words, problems will rarely have equal impact, so it

is best to first concentrate on the most important.

--- Content provided by​ FirstRanker.com ---



This does not provide a scientifically accurate estimation of the weightage with

respect to the range of alternatives. This reminds a manager to always look for

--- Content provided by FirstRanker.com ---


'the vital few' issues, and to separate them from 'the trivial many', before

attempting to solve problems. The next step is to identify which particular

--- Content provided by FirstRanker.com ---

problems are the most important. This is done by collecting appropriate data and

displaying it in the form of a histogram with each measured characteristic shown

in descending order of magnitude. Such a histogram is known as a Pareto chart.

--- Content provided by FirstRanker.com ---




Following is an example of a Pareto chart.

--- Content provided by⁠ FirstRanker.com ---


40

30

--- Content provided by​ FirstRanker.com ---

20

10

0

--- Content provided by​ FirstRanker.com ---




The high value items to the left hand side of the chart are the ones that are

--- Content provided by​ FirstRanker.com ---

needed to be concentrated on first.




--- Content provided by‍ FirstRanker.com ---


Some problems and difficulties associated with Pareto Analysis:



--- Content provided by‍ FirstRanker.com ---

Misrepresentation of the data.
Inappropriate measurements depicted.
Lack of understanding of how it should be applied to particular

problems.

--- Content provided by⁠ FirstRanker.com ---


Knowing when and how to use Pareto Analysis.
Inaccurate plotting of cumulative percent data.
Overcoming the difficulties.

--- Content provided by‌ FirstRanker.com ---



In conclusion


--- Content provided by‍ FirstRanker.com ---


Even in circumstances which do not strictly conform to the 80: 20 rule the

method is an extremely useful way to identify the most critical aspects on which

--- Content provided by⁠ FirstRanker.com ---

to concentrate. When used correctly Pareto Analysis is a powerful and effective


tool in continuous improvement and problem solving to separate the vital few`

--- Content provided by FirstRanker.com ---

from the many other` causes in terms of cost and/or frequency of occurrence.



It is the discipline of organizing the data that is central to the success of using

--- Content provided by‍ FirstRanker.com ---


Pareto Analysis. Once calculated and displayed graphically, it becomes a selling

tool to the improvement team and management, raising the question why the

--- Content provided by​ FirstRanker.com ---

team is focusing its energies on certain aspects of the problem.



Summary:

--- Content provided by‌ FirstRanker.com ---




Pareto analysis is a very simple technique that helps a manager to choose the

--- Content provided by⁠ FirstRanker.com ---

most effective changes to make. . This effect, known as the 80: 20 rules, can be

observed in action so often that it seems to be almost a universal truth.


--- Content provided by‍ FirstRanker.com ---


It is represented as a bar graph used to arrange information in such a way that

priorities for process improvement can be established. Pareto charts are

--- Content provided by⁠ FirstRanker.com ---

constructed to provide a before-and-after comparison of the effect of control or

quality improvement measures


--- Content provided by​ FirstRanker.com ---


Pareto charts provide a tool for visualizing the Pareto principle, which states that

a small set of problems (the "vital few") affecting a common outcome tend to

--- Content provided by‍ FirstRanker.com ---

occur much more frequently than the remainder (the "useful many"). A Pareto

chart can be used to decide which subset of problems should be solved first, or

which problems deserve the most attention.

--- Content provided by​ FirstRanker.com ---




Once calculated and displayed graphically, it becomes a selling tool to the

--- Content provided by‍ FirstRanker.com ---

improvement team and management, raising the question why the team is

focusing its energies on certain aspects of the problem.


--- Content provided by​ FirstRanker.com ---


Questions:



--- Content provided by‌ FirstRanker.com ---

1. What is Pareto principle?

2. What is the importance of this in Marketing?

3. What is Pareto effect? Explain.

--- Content provided by⁠ FirstRanker.com ---


4. How is Pareto charts created?

5. What are the advantages of creating Pareto charts?

--- Content provided by FirstRanker.com ---

6. What are the difficulties associated with the creation of Pareto charts?




--- Content provided by FirstRanker.com ---






--- Content provided by​ FirstRanker.com ---






--- Content provided by FirstRanker.com ---






--- Content provided by‌ FirstRanker.com ---




CHAPTER VI

--- Content provided by⁠ FirstRanker.com ---



ISHIKAWA DIAGRAMS


--- Content provided by FirstRanker.com ---


Objective:



--- Content provided by FirstRanker.com ---

The objective of this chapter is to understand:



Origin of Ishikawa Diagrams

--- Content provided by​ FirstRanker.com ---

Concept of Cause and Effect
Steps involved in creating an Ishikawa Diagram



--- Content provided by​ FirstRanker.com ---

Introduction:



Ishikawa Diagrams are a graphical method for finding the most likely causes for

--- Content provided by‌ FirstRanker.com ---


an undesired effect. The method was first used by Kaoru Ishikawa in the 1960s.



--- Content provided by​ FirstRanker.com ---

The Cause and Effect diagram also known as the "fishbone" or "Ishikawa"

diagram after its creator Kaoru Ishikawa is used to systematically list all the

different causes that can be attributed to a specific problem (or effect). A cause-

--- Content provided by‍ FirstRanker.com ---


and-effect diagram can help identify the reasons why a process goes out of

control.

--- Content provided by⁠ FirstRanker.com ---



Because of its shape, it is also known as the fishbone diagram. Another name for

this technique is: the cause-and-effect diagram. The fishbone diagram is a

--- Content provided by‌ FirstRanker.com ---


method/tool used in a root cause analysis.



--- Content provided by‍ FirstRanker.com ---

The Ishikawa diagram is one of the seven basic tools of quality control, which

include the histogram, Pareto chart, check sheet, control chart, cause-and-effect

diagram, flowchart, and scatter diagram.

--- Content provided by‍ FirstRanker.com ---




The purpose of this diagram is to arrive at a few key sources that contribute

--- Content provided by‍ FirstRanker.com ---

most significantly to the problem being examined. These sources are then

targeted for improvement. The diagram also illustrates the relationships among

the wide variety of possible contributors to the effect.

--- Content provided by‍ FirstRanker.com ---




The figure below shows a simple Ishikawa diagram

--- Content provided by‍ FirstRanker.com ---





Envi

--- Content provided by⁠ FirstRanker.com ---


E

ron

--- Content provided by‌ FirstRanker.com ---

r men

m t

Wor

--- Content provided by‌ FirstRanker.com ---


o ker

k s

--- Content provided by‌ FirstRanker.com ---



Too hot

h

--- Content provided by​ FirstRanker.com ---


Trai

a ning

--- Content provided by‌ FirstRanker.com ---

n



Unh

--- Content provided by‍ FirstRanker.com ---


U

app

--- Content provided by‌ FirstRanker.com ---

a y

Wor

o ker

--- Content provided by FirstRanker.com ---


k s



--- Content provided by‌ FirstRanker.com ---



old


--- Content provided by⁠ FirstRanker.com ---


Man

M agemen

--- Content provided by​ FirstRanker.com ---

em t

Machine

M

--- Content provided by‌ FirstRanker.com ---


s



--- Content provided by FirstRanker.com ---

The basic concept in the Cause-and-Effect diagram is that the name of a basic

problem of interest is entered at the right of the diagram at the end of the main

bone". The main possible causes of the problem (the effect) are drawn as

--- Content provided by‌ FirstRanker.com ---


bones off of the main backbone. The "Four-M" categories are typically used as

a starting point: "Materials", "Machines", "Manpower", and "Methods".

--- Content provided by‍ FirstRanker.com ---

Different names can be chosen to suit the problem at hand, or these general

categories can be revised. The key is to have three to six main categories that

encompass all possible influences. Brainstorming is typically done to add

--- Content provided by⁠ FirstRanker.com ---


possible causes to the main "bones" and more specific causes to the "bones" on

the main "bones". This subdivision into ever increasing specificity continues as

--- Content provided by​ FirstRanker.com ---

long as the problem areas can be further subdivided. The practical maximum

depth of this tree is usually about four or five levels. When the fishbone is

complete, one has a rather complete picture of all the possibilities about what

--- Content provided by‌ FirstRanker.com ---


could be the root cause for the designated problem.



--- Content provided by FirstRanker.com ---

The Cause-and-Effect diagram can be used by individuals or teams; probably

most effectively by a group. A typical utilization is the drawing of a diagram on

a blackboard by a team leader who first presents the main problem and asks for

--- Content provided by‍ FirstRanker.com ---


assistance from the group to determine the main causes which are subsequently

drawn on the board as the main bones of the diagram. The team assists by

--- Content provided by FirstRanker.com ---

making suggestions and, eventually, the entire cause and effect diagram is filled

out. Once the entire fishbone is complete, team discussion takes place to decide

on the most likely root causes of the problem. These causes are circled to

--- Content provided by​ FirstRanker.com ---


indicate items that should be acted upon, and the use of the tool is complete.



--- Content provided by⁠ FirstRanker.com ---

How to Construct an Ishikawa Diagram:



Place the main problem under investigation in a box on the right.

--- Content provided by‌ FirstRanker.com ---

Generate and clarify all the potential sources of variation.
Use an affinity diagram to sort the process variables into naturally

related groups. The labels of these groups are the names for the major

--- Content provided by‍ FirstRanker.com ---

bones on the Ishikawa diagram.

The process variables are then placed on the appropriate bones of the

Ishikawa diagram.

--- Content provided by‌ FirstRanker.com ---


Combine each bone in turn, insuring that the process variables are

specific, measurable, and controllable. If they are not, branch or

--- Content provided by‍ FirstRanker.com ---


"explode" the process variables until the ends of the branches are

specific, measurable, and controllable.

--- Content provided by‍ FirstRanker.com ---



The Ishikawa diagram, like most quality tools, is a visualization and knowledge

organization tool. Simply collecting the ideas of a group in a systematic way

--- Content provided by‍ FirstRanker.com ---


facilitates the understanding and ultimate diagnosis of the problem. Several

computer tools have been created for assisting in creating Ishikawa diagrams.

--- Content provided by⁠ FirstRanker.com ---



Summary:


--- Content provided by FirstRanker.com ---


Ishikawa Diagrams are a graphical method for finding the most likely causes for

an undesired effect.

--- Content provided by⁠ FirstRanker.com ---



The Cause and Effect diagram also known as the "fishbone" or "Ishikawa"

diagram after its creator Kaoru Ishikawa is used to systematically list all the

--- Content provided by‌ FirstRanker.com ---


different causes that can be attributed to a specific problem (or effect). A cause-

and-effect diagram can help identify the reasons why a process goes out of

--- Content provided by FirstRanker.com ---

control.



The Ishikawa diagram, like most quality tools, is a visualization and knowledge

--- Content provided by⁠ FirstRanker.com ---


organization tool. Simply collecting the ideas of a group in a systematic way

facilitates the understanding and ultimate diagnosis of the problem.

--- Content provided by​ FirstRanker.com ---



Questions:

1. What are Ishikawa diagrams?

--- Content provided by‍ FirstRanker.com ---


2. Ishikawa diagrams are useful tools in Marketing. Explain.

3. What are the considerations for creating an Ishikawa diagram?

--- Content provided by⁠ FirstRanker.com ---

4. List out the steps involved in the creation of Ishikawa diagram.


References for this Unit:

--- Content provided by FirstRanker.com ---



1. Naresh K. Malhotra: MARKETING RESEARCH: AN APPLIED

ORIENTATION, Pearson Education, Asia.

--- Content provided by FirstRanker.com ---


2. Aaker, Kumar & Day: MARKETING RESEARCH, John Wiley & Sons,

1998.

--- Content provided by FirstRanker.com ---

3. Paul E. Green & Donald S. Tull: RESEARCH FOR MARKETING

DECISIONS.

4. Carol S. Aneshensel; University of California, Los Angeles;

--- Content provided by‌ FirstRanker.com ---


UNIVARIATE ANALYSIS: CENTRAL TENDENCY, SPREAD,

AND ASSOCIATIONS

--- Content provided by⁠ FirstRanker.com ---

5. Cooley, W.W. and P. R. Lohnes. 1971. Multivariate Data Analysis. John

Wiley & Sons, Inc.

6. George H. Dunteman (1984). Introduction to multivariate analysis.

--- Content provided by FirstRanker.com ---


Thousand Oaks, CA: Sage Publications. Chapter 5 covers classification

procedures and discriminant analysis.

--- Content provided by‍ FirstRanker.com ---

7. Morrison, D.F. 1967. Multivariate Statistical Methods. McGraw-Hill:

New York.

8. Overall, J.E. and C.J. Klett. 1972. Applied Multivariate Analysis.

--- Content provided by‍ FirstRanker.com ---


McGraw-Hill: New York.

9. Tabachnick, B.G. and L.S. Fidell. 1996. Using Multivariate Statistics.

--- Content provided by‌ FirstRanker.com ---

Harper Collins College Publishers: New York.




--- Content provided by‍ FirstRanker.com ---