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Download UOC (University of Calicut) M.Com (Master of Commerce) Quantitative Techniques for Business Decision Question Bank (Important Questions)

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Calicut University M.Com 2020 Important Questions (Question Bank) || (University of Calicut)

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MULTIPLE CHOICE QUESTIONS ON QUANTITATIVE TECHNIQUES

The techniques which provide the decision maker a systematic and powerful means of analysis to explore policies for achieving predetermined goals are called........
1. Correlation techniques
2. Mathematical techniques
3. Quantitative techniques
4. None of the above
Correlation analysis is a .........................
1. Univariate analysis
2. Bivariate analysis
3. Multivariate analysis
4. Both b and c
If change in one variable results a corresponding change in the other variable, then the variables are....
1. Correlated
2. Not correlated
3. Any of the above
4. None of the above
When the values of two variables move in the same direction, correlation is said to be .........................
1. Linear
2. Non-linear
3. Positive
4. Negative
When the values of two variables move in the opposite directions, correlation is said to be .........................
1. Linear
2. Non-linear
3. Positive
4. Negative
When the amount of change in one variable leads to a constant ratio of change in the other variable, then correlation is said to be .........................
1. Linear
2. Non-linear
3. Positive
4. Negative
.........attempts to determine the degree of relationship between variables.
1. Regression analysis
2. Correlation analysis
3. Inferential analysis
4. None of these
Non-linear correlation is also called.........................
1. Non-curvy linear correlation
2. Curvy linear correlation
3. Zero correlation
4. None of these
Scatter diagram is also called .........................
1. Dot chart
2. Correlation graph
3. Both a and b
4. None of these
If all the points of a scatter diagram lie on a straight line falling from left upper corner to the right bottom corner, the correlation is called.........................
1. Zero correlation
2. High degree of positive correlation
3. Perfect negative correlation
4. Perfect positive correlation
If all the dots of a scatter diagram lie on a straight line falling from left bottom corner to the right upper corner, the correlation is called.........................
1. Zero correlation
2. High degree of positive correlation
3. Perfect negative correlation
4. Perfect positive correlation
Numerical measure of correlation is called .........................
1. Coefficient of correlation
2. Coefficient of determination
3. Coefficient of non-determination
4. Coefficient of regression
Coefficient of correlation explains:
1. Concentration
2. Relation
3. Dispersion
4. Asymmetry
Coefficient of correlation lies between:
1. 0 and +1
2. 0 and-1
3. -1 and +1
4. 3 and +3
A high degree of +ve correlation between availability of rainfall and weight of weight of people is:
1. A meaningless correlation
2. A spurious correlation
3. A nonsense correlation
4. All of the above
If the ratio of change in one variable is equal to the ratio of change in the other variable, then the correlation is said to be .........................
1. Linear
2. Non-linear
3. Curvilinear
4. None of these
Pearsonian correlation coefficient if denoted by the symbol ..........
1. K
2. r
3. R
4. None of these
If r= +1, the correlation is said to be .........................
1. High degree of +ve correlation
2. High degree of -ve correlation
3. Perfect +ve correlation
4. Perfect -ve correlation
If the dots in a scatter diagram fall on a narrow band, it indicates a ......................... degree of correlation.
1. Zero
2. High
3. Low
4. None of these
If all the points of a dot chart lie on a straight line vertical to the X-axis, then coefficient of correlation is .........................
1. 0
2. +1
3. -1
4. None of these
If all the points of a dot chart lie on a straight line parallel to the X-axis, it denotes .........................of correlation.
1. High degree
2. Low degree
3. Moderate degree
4. Absence
If dots are lying on a scatter diagram in a haphazard manner, then r = .........................
1. 0
2. +1
3. -1
4. None of these
The unit of Coefficient of correlation is .........................
1. Percentage
2. Ratio
3. Same unit of the data
4. No unit
Product moment correlation method is also called .........................
1. Rank correlation
2. Pearsonian correlation
3. Concurrent deviation
4. None of these
The -ve sign of correlation coefficient between X and Y indicates.........................
1. X decreasing, Y increasing
2. X increasing, Y decreasing
3. Any of the above
4. There is no change in X and Y
Coefficient of correlation explains .........................of the relationship between two variables.
1. Degree
2. Direction
3. Both of the above
4. None of the above
For perfect correlation, the coefficient of correlation should be .........................
1. ± 1
2. + 1
3. -1
4. 0
Rank correlation coefficient was discovered by.........................
1. Fisher
2. Spearman
3. Karl Pearson
4. Bowley
The rank correlation coefficient is always.........................
1. + 1
2. -1
3. 0
4. Between + 1 and -1
Spearman's Rank Correlation Coefficient is usually denoted by...............
1. k
2. r
3. S
4. R
Probable error is used to:
1. Test the reliability of correlation coefficient
2. Measure the error in correlation coefficient
3. Both a an b
4. None of these
If coefficient of correlation is more than .........................of its P E, correlation is significant.
1. 2 times
2. 5 times
3. 6 times
4. 10 times
In correlation analysis, Probable Error = ......................... x 0.6745
1. Standard deviation
2. Standard error
3. Coefficient of correlation
4. None of these
Coefficient of concurrent deviation depends
1. The signs of the deviations
2. The magnitude of the deviation
3. Bothe a and b
4. None of these
Correlation analysis between two sets of data only is called.........................
1. Partial correlation
2. Multiple correlation
3. Nonsense correlation
4. Simple correlation
Correlation analysis between one dependent variable with one independent variable by keeping the other independent variables as constant is called.........................
1. Partial correlation
2. Multiple correlation
3. Nonsense correlation
4. Simple correlation
Study of correlation among three or more variables simultaneously is called.............
1. Partial correlation
2. Multiple correlation
3. Nonsense correlation
4. Simple correlation
If r = 0.8, coefficient of determination is.....
1. 80%
2. 8%
3. 64%
4. 0.8%
If r is the simple correlation coefficient, the quantity r² is known as .........................
1. Coefficient of determination
2. Coefficient of non-determination
3. Coefficient of alienation
4. None of these
If r is the simple correlation coefficient, the quantity 1 -- r² is known as .........................
1. Coefficient of determination
2. Coefficient of non-determination
3. Coefficient of alienation
4. None of these
The term regression was first used by.........................
1. Karl Pearson
2. Spearman
3. R A Fisher
4. Francis Galton
.........................refers to analysis of average relationship between two variables to provide mechanism for prediction.
1. Correlation
2. Regression
3. Standard error
4. None of these
If there are two variables, there can be at most......................... number of regression lines.
1. One
2. Two
3. Three
4. Infinite
If the regression line is Y on X, then the variable X is known as.........................
1. Independent variable
2. Explanatory variable
3. Regressor
4. All the above
Regression line is also called.........................
1. Estimating equation
2. Prediction equation
3. Line of average relationship
4. All the above
If the regression line is X on Y, then the variable X is known as.........................
1. Dependent variable
2. Explained variable
3. Both a and b
4. Regressor
If the regression line is X on Y, then the variable X is known as.........................
1. Dependent variable
2. Independent variable
3. Bothe a and b
4. None of the above
If the regression line is Y on X, then the variable X is known as.........................
1. Dependent variable
2. Independent variable
3. Both a and b
4. None of the above
The point of intersection of two regression lines is.........................
1. (0,0)
2. (1,1)
3. (x,y)
4. (x¯, y¯)
If r = ± 1, the two regression lines are.........................
1. Coincident
2. Parallel
3. Perpendicular to each other
4. None of these
If r = 1, the angle between the two regression lines is.........................
1. Ninety degree
2. Thirty degree
3. Zero degree
4. Sixty degree
If r = 0, the two regression lines are:
1. Coincident
2. Parallel
3. Perpendicular to each other
4. None of these
If bxy and byx are two regression coefficients, they have:
1. Same signs
2. Opposite signs
3. Either a or b
4. None of the above.
If byx > 1, then bxy is:
1. Greater than one
2. Less than one
3. Equal to one
4. Equal to zero
If X and Y are independent, the value of byx is equal to .........................
1. Zero
2. One
3. Infinity
4. Any positive value
The property that both the regression coefficients and correlation coefficient have same signs is called.........................
1. Fundamental property
2. Magnitude property
3. Signature property
4. None of these
The property that byx > 1 implies that bxy < 1 is known as .........................
1. Fundamental property
2. Magnitude property
3. Signature property
4. None of these
If X and Y are independent, the property byx = bxy = 0 is called .........................
1. Fundamental property
2. Magnitude property
3. Mean property
4. Independence property
The Correlation coefficient between two variables is the ......................... of their regression coefficients.
1. Arithmetic mean
2. Geometric mean
3. Harmonic mean
4. None of these
If the correlation coefficient between two variables, X and Y, is negative, then the regression coefficient of Y on X is........
1. Positive
2. Negative
3. Not certain
4. None of these
The G M of two regression coefficients byx and bxy is equal to .........................
1. r
2. r²
3. 1-r²
4. None of these
If one regression coefficient is negative, the other is .........................
1. 0
2. - ve
3. +ve
4. Either a or b
Arithmetic mean of the two regression coefficients is:
1. Equal to correlation coefficient
2. Greater than correlation coefficient
3. Less than correlation coefficient
4. Equal to or greater than correlation coefficient
byx is the regression coefficient of the regression equation.........................
1. Y on X
2. X on Y
3. Either a or b
4. None of these
bxy is the regression coefficient of the regression equation.........................
1. Y on X
2. X on Y
3. Either a or b
4. None of these
In ......................... regression analysis, only one independent variable is used to explain the dependent variable.
1. Multiple
2. Non-linear
3. Linear
4. None of these
The regression coefficient and correlation coefficient of the two variables will be the same if their .........................are same.
1. Arithmetic mean
2. Standard deviation
3. Geometric mean
4. Mean deviation
The idea of testing of hypothesis was first set forth by .........................
1. R A Fisher
2. J Neyman
3. E L Lehman
4. A Wald
By testing of hypothesis, we mean:
1. A significant procedure in Statistics
2. A method of making a significant statement
3. A rule for accepting or rejecting hypothesis
4. A significant estimation of a problem.
Testing of hypothesis and .........................are the two branches of statistical inference.
1. Statistical analysis
2. Probability
3. Correlation analysis
4. Estimation
......................... is the original hypothesis
1. Null hypothesis
2. Alternative hypothesis
3. Either a or b
4. None of these
A null hypothesis is denoted by.........................
1. Ho
2. H1
3. NH
4. None of these
An alternative hypothesis is denoted by.........................
1. Ho
2. H1
3. AH
4. None of these
Whether a test is one sided or two sided, depends on.........................
1. Simple hypothesis
2. Composite hypothesis
3. Null hypothesis
4. Alternative hypothesis
A wrong decision about null hypothesis leads to:
1. One kind of error
2. Two kinds of errors
3. Three kinds of errors
4. Four kinds of errors
Power of a test is related to .........................
1. Type I error
2. Type II error
3. Both a and b
4. None of these
Level of significance is the probability of.........................
1. Type I error
2. Type II error
3. Both a and b
4. None of these
Which type of error is more severe error:
1. Type I error
2. Type II error
3. Both a and b
4. None of these
Type II error means.........................
1. Accepting a true hypothesis
2. Rejecting a true hypothesis
3. Accepting a wrong hypothesis
4. Rejecting a wrong hypothesis
Type I error is denoted by............
1. Alpha
2. Beta
3. Gamma
4. None of these
Type II error is denoted by.........................
1. Alpha
2. Beta
3. Gamma
4. None of these
The level of probability of accepting a true null hypothesis is called.........................
1. Degree of freedom
2. Level of significance
3. Level of confidence
4. D,
The probability of rejecting a true null hypothesis is called .........................
1. Degree of freedom
2. Level of significance
3. Level of confidence
4. None of these
1-Level of confidence =.........................
1. Level of significance
2. Degree of freedom
3. Either a or b
4. None of these
While testing a hypothesis, if level of significance is not mentioned, we take ......................... level of significance.
1. 1%
2. 2%
3. 5%
4. 10%
A sample is treated as large sample, when its size is.........................
1. More than 100
2. More than 75
3. More than 50
4. More than 30
.........................refers to the number of independent observations which is obtained by subtracting the number of constraints from the total number of observations.
1. Sample size
2. Degree of freedom
3. Level of significance
4. Level of confidence
Total number of observations - number of constraints =.........................
1. Level of significance
2. Degree of freedom
3. Level of confidence
4. Sample size
Accepting a null hypothesis when it is false is called.........................
1. Type I error
2. Type II error
3. Probable error
4. Standard error
Accepting a null hypothesis when it is true is called.........................
1. Type I error
2. Type II error
3. Probable error
4. No error
When sample is small, ......................... test is applied.
1. t-test
2. Z test
3. F test
4. None of these
To test a hypothesis about proportions of items in a class, the usual test is..............
1. t-test
2. Z- test
3. F test
4. Sign test
Student's t-test is applicable when:
1. The values of the variate are independent
2. The variable is distributed normally
3. The sample is small
4. All the above
Testing of hypotheses H? : µ = 45 vs. H1 : µ > 45 when the population standard deviation is known, the appropriate test is:
1. t-test
2. Z test
3. Chi-square test
4. F test
Testing of hypotheses Ho : µ = 85 vs. H1 : µ > 85, is a .........................test.
1. One sided left tailed test
2. One sided right tailed test
3. Two tailed test
4. None of these
Testing of hypotheses Ho : µ = 65 vs. H1 : µ < 65, is a .........................test
1. One sided left tailed test
2. One sided right tailed test
3. Two tailed test
4. None of these
Testing of hypotheses Ho : µ = 65 vs. H1: µ? 65, is a .........................test.
1. One sided left tailed test
2. One sided right tailed test
3. Two tailed test
4. None of these
Student's t-test was designed by.........................
1. R A Fisher
2. Wilcoxon
3. Wald wolfowitz
4. W S Gosset
Z test was designed by .........................
1. R A Fisher
2. Wilcoxon
3. Wald wolfowitz
4. W S Gosset
Z test was designed by .........................
1. R A Fisher
2. Wilcoxon
3. Wald wolfowitz
4. W S Gosset
The range of F ratio is .........................
1. - 1 to + 1
2. -8 to 8
3. 0 to 8
4. 0 to 1
While computing F ratio, customarily, the larger variance is taken as .........................
1. Denominator
2. Numerator
3. Either way
4. None of these
Chi-square test was first used by .........................
1. R A Fisher
2. William Gosset
3. James Bernoulli
4. Karl Pearson
The Chi-squre quantity ranges from ......................... to .........................
1. - 1 to +1
2. -8 to 8
3. 0 to 8
4. 0 to 1
Degrees of freedom for Chi-squre test in case of contingency table of order (2x2) is:
1. 4
2. 3
3. 2
4. 1
Degrees of freedom for Chi-squre test in case of contingency table of order (4x3) is:
1. 4
2. 3
3. 6
4. 7
Degrees of freedom for Chi-squre test in case of contingency table of order (5x5) is:
1. 25
2. 16
3. 10
4. Infinity
The magnitude of the difference between observed frequencies and expected frequencies is called .........................
1. F value
2. Z value
3. t value
4. Chi-square value
When the expected frequencies and observed frequencies completely coincide, the chi-square value will be .........................
1. + 1
2. -1
3. 0
4. None of these
If the discrepancy between observed and expected frequencies are greater, ......................... will be the chi-square value.
1. Greater
2. Smaller
3. Zero
4. None of these
Calculated value of chi-square is always.........................
1. Positive
2. Negative
3. Zero
4. None of these
While applying chi-square test, the frequency in any cell should not be .........................
1. More than 5
2. Less than 5
3. More than 10
4. Less than 10
Analysis of variance utilises.........................
1. F test
2. Chi square test
3. Z test
4. t test
In one way ANOVA, the variances are:
1. Within samples
2. Between samples
3. Total
4. All
The technique of analysis of variance was developed by .........................
1. Frank Wilcoxon
2. Karl Pearson
3. R A Fisher
4. Kolmogrov
Non-parametric test is :
1. Distribution free test
2. Not concerned with parameter
3. Does not depend on the particular form of the distribution
4. None of these
.........................tests follow assumptions about population parameters.
1. Parametric
2. Non-parametric
3. One-tailed
4. Two-tailed
.........................is the simplest and most widely used non-parametric test
1. Sign test
2. K-S test
3. Chi-square tst
4. Wilcoxon matched paired test
Runs test was designed by .........................
1. Kruskal and Wallis
2. Kolmogrov and Smirnov
3. Wald wolfowitz
4. Karl Pearson
Which one of the following is a non-parametric test?
1. F test
2. Z test
3. t test
4. Wilcoxon test
Control charts are also termed as.........................
1. Shewart charts
2. Process behaviour chart
3. Both a and b
4. None of these
What type of chart will be used to plot the number of defective in the output of any process?
1. x chart
2. R chart
3. C chart
4. P chart
Process control is carried out:
1. Before production
2. During production
3. After production
4. All of the above
The dividing lines between random and non-random deviations from mean of the distribution are known as .........................
1. Upper Control Limit
2. Lower Control Limit
3. Control Limits
4. Two sigma limit
The control charts used to monitor variable is.........................
1. Range chart
2. P-chart
3. C-chart
4. All of the above
The control charts used to monitor attributes is.........................
1. Range chart
2. P-chart
3. C-chart
4. All of the above
The control charts used for the fraction of defective items in a sample is.........................
1. Range chart
2. P-chart
3. C-chart
4. Mean chart
The control charts used for the number of defects per unit is:
1. Range chart
2. P-chart
3. C-chart
4. Mean chart
.........................is user for testing goodness of fit.
1. Wilcoxon test
2. Sign test
3. K-S Test
4. Chi-square test

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This post was last modified on 26 December 2019

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