GTU · BE IT · Semester 5
GTU 3151608 Data Science Old Question Papers PDF
Official Gujarat Technological University (GTU) old question papers PDF (Regular & Remedial) and step-by-step solved questions for Data Science across 2023 – 2026 examinations.
38 questions GTU asked more than onceAsked in 6 of 7 papers: Explain various measures of shapes with suitable examples.See listExam papers
Most repeated questions
38 questions GTU set in two or more of 7 papers, most repeated first. Tap a year to open that paper at the question.
Explain various measures of shapes with suitable examples.
Summer 2026 Q2c OR Winter 2025 Q3b Summer 2025 Q3b Winter 2024 Q4c Summer 2024 Q4c Winter 2023 Q2b
Why is the choice of measurement scale important in statistical analysis? Explain nominal, ordinal, interval, and ratio scales with examples.
Summer 2026 Q3c Winter 2025 Q2b Summer 2024 Q4a OR Summer 2023 Q1c
Discuss decision tree algorithm for classification of data with example.
Winter 2025 Q5c Summer 2025 Q5c OR Winter 2023 Q4c OR Summer 2023 Q5c OR
Explain Random Forest method with suitable example
Winter 2025 Q5c OR Summer 2025 Q5a OR Summer 2024 Q5c Winter 2023 Q5c
Discuss CLT-Central Limit Theorem.
Summer 2026 Q3b Summer 2025 Q4c OR Summer 2024 Q3b OR Winter 2023 Q3b
Differentiate Probabilistic Sampling and Non-Probability Sampling.
Winter 2025 Q4b Winter 2024 Q2b Winter 2023 Q4a Summer 2023 Q3b
Explain Outlier analysis in brief.
Winter 2025 Q5b OR Winter 2024 Q4a Summer 2024 Q3a OR Winter 2023 Q5a
What is probability mass function ? Define pdf and cdf for continuous random variable.
Summer 2025 Q3b OR Winter 2024 Q2c Summer 2024 Q3c OR Winter 2023 Q2c
Explain how Maximum Likelihood Estimation can be used to estimate parameters.
Summer 2026 Q3a Winter 2025 Q4c OR Winter 2024 Q4c OR Winter 2023 Q4b OR Winter 2023 Q5c OR
State Bayes’ Theorem.
Summer 2026 Q2a Winter 2025 Q4a Summer 2025 Q3c Winter 2024 Q3c
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When percentile is preferred over percentage? Explain percentile, quartile and decile with examples.
Explain various measures of central tendency with suitable examples.
Differentiate Chi-Square Distribution, Student’s t-Distribution and F-Distribution.
Discuss how descriptive, predictive and prescriptive analytics techniques can be applied in healthcare applications. Explain with simple examples.
Explain why Central Limit Theorem is called as a heart of the Data Science.
Discuss Method of Moments.
Compare linear regression vs. Logistic regression.
Differentiate stratified and cluster sampling.
What is difference between correlation and regression.
Explain the categories of Machine Learning Algorithms.
Define population and sample.
Define random variable. Explain the types of random variable by taking suitable example.
What is linear regression? Explain with example.
List out the major categories of Sampling Method. Explain in detail.
Explain how the Chi-Square Automatic Interaction Detection (CHAID) method works in splitting decision tree nodes.
Discuss the framework for Data-Driven Decision Making and Analytics Capability Building.
What is Probability Distribution function? Explain Uniform Distribution, Normal Distribution, and Exponential Distribution in brief.
Explain Simple Linear Regression model building steps.
Explain steps for validation of Simple Linear Regression model.
Differentiate Sensitivity and Specificity.
Differentiate Gain Chart and Lift Chart
What is Weight and Bias Tradeoff in Linear Regression?
Discuss the advantages and limitations of Ensemble Methods like Random Forest in classification.
Explain significance of GINI impurities in splitting dataset.
Discuss Poisson distribution with example
State difference between structure data and unstructured data.
Define Entropy, Information Gain and Gini Index.
Explain chebyshev theorem with example.
Which branches take this subject
GTU's syllabus lists 3151608 for 2 branches. One set of papers serves all of them.
Semester 5, elective: 2 branches
Computer Science & Engineering (Cyber Security), Information Technology
Other Semester 5 subjects
Common questions
Are these GTU 3151608 Data Science papers valid for both Regular and Remedial exams?
Yes. Gujarat Technological University (GTU) follows the same 70-mark syllabus, exam blueprint, and 23-mark passing cutoff for both Regular and Remedial (ATKT/backlog) examinations. All 7 past exam sessions (2023 – 2026) serve as comprehensive preparation for either attempt.
How can I download GTU 3151608 Data Science old question papers PDF?
You can download official GTU 3151608 original question paper PDFs directly from the table above with 1 click and zero deceptive ads or wait timers. Every paper also includes interactive online questions with AI study prompts.
What is the passing mark for GTU Data Science (3151608)?
The external theory exam carries 70 marks. The minimum passing cutoff is 23 marks (33%). Exam duration is 2.5 hours.
What is the GTU exam pattern for 3151608?
The examination contains 5 main questions of 14 marks each, totaling 70 marks. Questions 2 through 5 provide internal OR choices, typically split into 3-mark, 4-mark, and 7-mark questions.