Download GTU B.Tech 2020 Winter 5th Sem 3151608 Data Science Question Paper

Download GTU (Gujarat Technological University Ahmedabad) B.Tech/BE (Bachelor of Technology/ Bachelor of Engineering) 2020 Winter 5th Sem 3151608 Data Science Previous Question Paper

Seat No.: ________
Enrolment No.___________
GUJARAT TECHNOLOGICAL UNIVERSITY
BE- SEMESTER?V (NEW) EXAMINATION ? WINTER 2020
Subject Code:3151608 Date:22/01/2021
Subject Name:Data Science
Time:10:30 AM TO 12:30 PM Total Marks: 56
Instructions:
1. Attempt any FOUR questions out of EIGHT questions.

2. Make suitable assumptions wherever necessary.

3. Figures to the right indicate full marks.


MARKS
Q.1 (a) Define business analytics and explain the use of it.
03

(b) Give the difference between descriptive analytics and predictive
04
analytics.

(c) Explain the Framework for Data-Driven Decision Making process.
07


Q.2 (a) Define continuous random variable and discrete random variable with
03
example.

(b) Explain different categories of data.
04

(c) Explain Probability Density Function (PDF) and Cumulative
07
Distribution Function (CDF) of a Continuous Random Variable with
suitable example.




Q.3 (a) Below is the dataset of Pizza Price in given cities .Find Mean and
03
Median of both the cities.

(b) What is the need of Skewness and Kurtosis. Explain its types with
04
example.

(c) How the Chi-square distribution is differ from student's t-distribution
07
explain with example.




Q.4 (a) Give the difference between Probabilistic Sampling and Non-Probability
03
Sampling.

(b) Explain why Central Limit Theorem is called as a heart of the Data
04
Science.
1

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(c) Explain the importance of Sensitivity and specificity in logistic
07
regression Classification Table.



Q.5 (a) Explain different types of Data Measurement scales.
03

(b) How do you calculate maximum likelihood estimation?
04

(c) Explain Simple Linear Regression model with example.
07



Q.6 (a) What is Outlier Analysis explain in detail.
03

(b) Compare linear regression vs. Logistic regression.
04

(c) Explain the Validation process of the Simple Linear Regression Model.
07



Q.7 (a) How to select Variable Selection in Logistic Regression.
03

(b) Explain pros and cons of Decision Tree algorithm.
04

(c) Explain Decision tree algorithm with suitable example.
07



Q.8 (a) Which classification algorithm is preferable when number of records are
03
very large, random forest/ decision tree. Justify your answer.
(b) Explain Chi-Square Automatic Interaction Detection (CHAID) in detail.
04
(c) Explain Random forest algorithm with suitable example.
07

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