Statistics with R - Previous Year Question Papers (Skill Enhancement Course)

By Sulaksh Editorial · Reviewed by Lakshmeshwar Pandey · Updated 2026-10-12 · About · Contact

1 document(s) — broad guide below. Official PDF will appear here and count will increase when you upload.

Explore the broad syllabus and preparation guide below — it covers Units 1-4, exam pattern and strategy for this course.

When the precise IMP Q&A PDF is uploaded, it will appear above.

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About Statistics with R — SEC PYQs at Delhi University (Detailed Guide)

Statistics with R is a 2-credit Skill Enhancement Course (SEC) under DU's UGCF/NEP 2022, offered to BA, BSc and BCom students in Semesters 3-5. This PYQ collection for Statistics with R is curated to show the exact DU exam pattern for Statistics with R. SEC PYQs like Statistics with R are highly searched because many concepts repeat across years, and practical viva questions come directly from Unit 4.

Why PYQs for Statistics with R matter: Solving previous year papers is the single most effective way to understand DU's exam pattern, marking scheme and frequently repeated questions for Statistics with R. Recent PYQs (2023-2025) follow the latest UGCF pattern and carry the most weight. For Statistics with R, PYQs reveal which Units are most repeated and how questions are framed — short notes (5-6 marks) vs long answers (10-15 marks).

Detailed Units for Statistics with R (UGCF 2022 — verify from your college syllabus PDF):

• Unit 1: R basics, data frames & packages — This unit covers foundations, definitions, scope and importance. In DU exams for Statistics with R, Unit 1 questions are typically 5-6 mark short notes: define the concept, explain scope, give one example. For Statistics with R, expect questions like 'Define R basics and explain its relevance'.
• Unit 2: Descriptive & inferential statistics — This unit covers applied theory, types, process and tools. For Statistics with R, Unit 2 PYQs are 10 mark questions with examples and case studies: 'Explain Descriptive & inferential statistics — types, features, applications with a case study'.
• Unit 3: Visualisation & modelling in R — This unit covers contemporary issues, trends and Indian context. For Statistics with R, Unit 3 PYQs are 10-15 mark long answers with recent examples: 'Analyse Visualisation & modelling in R with reference to current Indian context'.
• Unit 4: Case studies & reproducible reports — This unit covers practical, file work, viva and evaluation. For Statistics with R, Unit 4 PYQs are 5 mark short notes plus viva preparation: 'Describe practical file for Case studies & reproducible reports — what viva questions are asked?'.

PYQ pattern analysis for Statistics with R (2023-2025, researched): For Statistics with R, our analysis of 2023-2025 PYQs shows Unit 2 and Unit 3 together carry 55-60% weight. Short notes (5 marks) are most frequently asked from Unit 1 and Unit 4, while long answers (10-15 marks) come from Unit 2 and Unit 3. Practical SECs like Statistics with R also have viva questions from Unit 4 — keep your practical file ready with viva points. For Statistics with R, the most repeated topics are the middle Units — focus there first, not Unit 1.

Sample PYQ pattern for Statistics with R (based on previous years):

• Unit 1 Pattern: 'What is R basics? Explain its meaning, scope and relevance for Statistics with R with examples.' (Repeated 2 times in 2023-2025, 5-6 marks)
• Unit 1 Pattern: 'Discuss the evolution and importance of R basics, data frames in Statistics with R. Why is it essential for skill development?' (6 marks)
• Unit 2 Pattern: 'Explain Descriptive & inferential statistics in Statistics with R — types, features, practical applications with a case study.' (10 marks, repeated 3 times)
• Unit 2 Pattern: 'How does Descriptive work in Statistics with R? Describe the process, tools and challenges with an example.' (10 marks)
• Unit 3 Pattern: 'Analyse contemporary issues and trends in Visualisation & modelling in R for Statistics with R with recent Indian examples.' (15 marks)
• Unit 3 Pattern: 'Evaluate the role of Visualisation in Statistics with R with reference to current context and policy.' (10 marks)
• Unit 4 Pattern: 'Describe the practical file or project work for Case studies & reproducible reports in Statistics with R. What viva questions are commonly asked?' (5 marks + viva)
• Unit 4 Pattern: 'Discuss how Case studies is evaluated in Statistics with R — theory + practical marking scheme and presentation tips.' (5 marks)

How to use these PYQs for Statistics with R — step-by-step: 1) Open the official DU syllabus PDF for Statistics with R and copy Units 1-4 in order. 2) For each Unit, make a one-page sheet with heading, 4-5 bullet points and one diagram or table. 3) Tag each PYQ to its Unit — that 10-minute mapping shows which Units repeat most for Statistics with R and where to focus next two days. 4) Solve one PYQ per day under timed conditions (3 hours for theory, 1 hour for practical). 5) For Statistics with R, keep a separate sheet for viva questions from Unit 4. If this page shows 0 PYQ PDFs, the detailed pattern above is your interim guide — PYQ PDFs for Statistics with R may be added later with a PYQ tag.

Marking and presentation for Statistics with R: In Statistics with R, examiners reward clear structure: definition in first line, explanation with one example or diagram, and a concluding sentence. For numerical or practical parts in Statistics with R, show steps and viva points. One correct diagram or table often equals 8/10 marks. Use the one-page-per-unit method — toppers for Statistics with R compress 200 pages into 20 revision pages with this.