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Gujarat Technological UniversitySummer 2026 Examination

GTU 3151608 Data Science Summer 2026 Paper Solution & PDF

B.E. · IT Engineering · Semester 5 · Subject Code: 3151608
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Total Marks70 MarksExternal theory exam
Passing Marks23 Marks33% minimum cutoff
Exam Duration2.5 Hours2:30 PM – 5:00 PM
Paper Structure5 QuestionsWith internal OR choices
Jump toQ1Q2Q3Q4Q5

Question 1

14 MarksMedium
(a)
Define population and sample.
3 Marks
(b)
Differentiate Cross-sectional, Time Series and Panel Data.
4 Marks
(c)

Discuss how descriptive, predictive and prescriptive analytics techniques can be applied in healthcare applications. Explain with simple examples.

7 Marks

Question 2

14 MarksMedium
(a)
State Bayes’ Theorem.
3 Marks
(b)
What is estimation? Differentiate point estimation and interval estimation.
4 Marks
(c)
Explain various measures of central tendency with suitable examples.
7 Marks
OR OPTION
(c)
Explain various measures of shapes with suitable examples.
7 Marks

Question 3

14 MarksMedium
(a)
Explain how Maximum Likelihood Estimation can be used to estimate parameters.
3 Marks
(b)
Discuss CLT-Central Limit Theorem.
4 Marks
(c)

Why is the choice of measurement scale important in statistical analysis? Explain nominal, ordinal, interval, and ratio scales with examples.

7 Marks
OR OPTION
(a)
Explain how sampling distribution can be used to make statistical inferences.
3 Marks
(b)
Discuss Method of Moments.
4 Marks
(c)

When percentile is preferred over percentage? Explain percentile, quartile and decile with examples.

7 Marks

Question 4

14 MarksMedium
(a)
Discuss applications of linear regression in data science.
3 Marks
(b)
Explain Simple Linear Regression model building steps.
4 Marks
(c)
Differentiate discrete and continuous probability distributions.
7 Marks
OR OPTION
(a)
Discuss purpose of Ordinary Least Squares method in linear regression.
3 Marks
(b)
Explain steps for validation of Simple Linear Regression model.
4 Marks
(c)
Differentiate Chi-Square Distribution, Student’s t-Distribution and F-Distribution.
7 Marks

Question 5

14 MarksMedium
(a)
Explain how logistic regression can be used in credit rating.
3 Marks
(b)
Differentiate Gain Chart and Lift Chart
4 Marks
(c)

A retail company wants to predict whether a customer will buy a product based on features such as age, income, past purchase history, etc. Explain how decision tree method can be applied to build this model.

7 Marks
OR OPTION
(a)
Explain purpose of Optimal Cut-Off Probability in logistic regression.
3 Marks
(b)
Differentiate Sensitivity and Specificity.
4 Marks
(c)

A bank wants to predict whether a customer will repay a loan on time using features such as income, credit history, age, and employment status. Explain how bagging, random forests, and boosting can be applied to improve the accuracy of this prediction.

7 Marks
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About this Examination Paper & Attribution

Official Gujarat Technological University (GTU) examination paper and step-by-step solutions for Data Science (Summer 2026, B.E. · IT Engineering, Sem 5). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.

Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.

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