GUJARAT TECHNOLOGICAL UNIVERSITY
BE- SEMESTER-V (NEW) EXAMINATION - WINTER 2020
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Subject Code:3151608 Date:22/01/2021Subject Name:Data Science
Time:10:30 AM TO 12:30 PM Total Marks: 56
Instructions:
- Attempt any FOUR questions out of EIGHT questions.
- Make suitable assumptions wherever necessary.
- Figures to the right indicate full marks.
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MARKS
Q.1 (a) Define business analytics and explain the use of it. 03
(b) Give the difference between descriptive analytics and predictive analytics. 04
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(c) Explain the Framework for Data-Driven Decision Making process. 07
Q.2 (a) Define continuous random variable and discrete random variable with example. 03
(b) Explain different categories of data. 04
(c) Explain Probability Density Function (PDF) and Cumulative Distribution Function (CDF) of a Continuous Random Variable with suitable example. 07
Q.3 (a) Below is the dataset of Pizza Price in given cities .Find Mean and Median of both the cities. 03
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places New Delhi Lucknow 1 118 135 2 228 235 3 338 335 4 358 435 5 438 535 6 558 635 7 658 735 8 758 835 9 958 935 10 1158 1035 11 665
(b) What is the need of Skewness and Kurtosis. Explain its types with example. 04
(c) How the Chi-square distribution is differ from student’s t-distribution explain with example. 07
Q.4 (a) Give the difference between Probabilistic Sampling and Non-Probability Sampling. 03
(b) Explain why Central Limit Theorem is called as a heart of the Data Science. 04
(c) Differentiate between the Regression and Classification Table. 07
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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
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(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 very large, random forest/ decision tree. Justify your answer. 03
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(b) Explain Chi-Square Automatic Interaction Detection (CHAID) in detail. 04
(c) Explain Random forest algorithm with suitable example. 07
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