References
Every source this site was built from, what was taken from each, and an honest list of the gaps and contradictions found along the way.
Chapter, section, page and slide numbers are read off the actual files, not inferred from a contents list. Where a location could not be verified, none is given. Where two supplied sources contradict each other, both are shown and the discrepancy is flagged rather than quietly resolved.
Click any citation anywhere on this site to open the exact page in a panel on the right.
Sources rendered into the viewer
645 pages and slides, from 16 documents:
Lecture decks (5 files, 231 slides)
| Deck | Slides | Covers | Open |
|---|---|---|---|
| Unit 1,2 Introduction n Summarization.pptx | 49 | What statistics is · data types and sources · classification · frequency, relative and percent distributions · bar, pie, stem-and-leaf, scatter · the tabular/graphical decision tree | Open |
| Unit 3_probab_intro.pptx | 44 | Likelihood scale · sample spaces · counting rules · three methods of assigning probability · complement, union, intersection · addition, conditional, multiplication · independence · total probability and Bayes | Open |
| Prob_Dis_Unit 4.ppt | 51 | Random variables · expected value and the lottery example · pmf, CDF, pdf · binomial · Poisson · normal · standardising · normal approximation to the binomial | Open |
| Sampling Dist.pptx | 44 | Statistic vs parameter · sampling distribution of the mean · CLT · standard error · sampling distribution of a proportion · finite population multiplier · and then estimation and the t distribution, which are Units 7–8 | Open |
| Sample Size Determination.pptx | 43 | Titled "Unit 6 (Part II)" · dispersion and the SD · the normal and standardised normal · population/sample/sampling distributions · CLT · precision vs confidence · factors setting sample size · both sample-size formulas · Roscoe's thumb rules | Open |
Decks were converted from PowerPoint to PDF with LibreOffice and rendered slide by slide. Slide numbers on this site are the slide's position in the deck as converted.
Your handwritten class notes (5 files, 36 pages)
| File | Pages | What is on them | Open |
|---|---|---|---|
| Chap 1_260723_221103.pdf | 5 (3 written) | The analysis tree (descriptive / predictive / prescriptive) · margin of error μ = x̄ ± 3σ/√n · the 95% and 99% confidence bands worked as an example · the error-vs-sample-size curve · a note that hypothesis testing answers yes/no, not a value | Open |
| Chap 2 Measures of Dispersion_260730.pdf | 7 (5 written) | Range/variance/SD as the three dispersion tools · coefficient of variation · skewness tree and sign rule · kurtosis and the three curves · Chebyshev's theorem · the Georgia hospital grouped mean worked to μ = 7.7 and its Chebyshev continuation | Open |
| Notes_260806_110504.pdf | 3 (2 written) | Law of total probability · Bayes' theorem · the entire proof · the heart-attack Bayes example worked to 60% | Open |
| Unit 4 Probability Distribution_260827.pdf | 11 (9 written) | Expected value · binomial formula and three worked problems · Poisson formula and two worked problems · normal distribution with curves drawn twice · normal approximation to the binomial, checked against the exact answer · the accounting-firms "at least one" case | Open |
| Sampling Distribution_260903_104238.pdf | 10 (8 written) | Definition and the five-employee sampling distribution built by hand · CLT · standard error · the bank-employees problem worked twice · finite population multiplier · sampling distribution of a proportion and the SVKM problem | Open |
These are scans with no text layer, so nothing in them is machine-searchable — every reference to them on this site was read off the image by eye. They are the most authoritative source for method, because they show how your lecturer actually lays a solution out and which z-table convention is expected.
Textbook (349 pages rendered)
Only the chapters Units 1–6 draw on are rendered, to keep the site to a sane size:
| Chapter | Printed pages | Unit | Open |
|---|---|---|---|
| 2 — Grouping and Displaying Data to Convey Meaning | 13–72 | 1 | Open |
| 3 — Measures of Central Tendency and Dispersion | 73–151 | 1–2 | Open |
| 4 — Probability I: Introductory Ideas | 153–206 | 3 | Open |
| 5 — Probability Distributions | 207–265 | 4 | Open |
| 6 — Sampling and Sampling Distributions | 267–314 | 5–6 | Open |
| 7 — Estimation (§7.8 is sample size) | 315–363 | 6 (Part II) | §7.8, p. 351 |
All page numbers on this site are the printed page numbers, which is what the book's own index and contents use. The PDF's internal page numbering runs 15 ahead (printed page 18 is PDF page 33), and the source viewer's "File ↗" button applies that offset automatically. Chapters 8–16 are in the book but outside the mid-term portion, so they are not rendered.
Question papers and answer keys (4 files, 26 pages)
| Document | Date | Pages | Open |
|---|---|---|---|
| Final Examination — Question Paper | 29 Nov 2025 | 7 | Open |
| Final Examination — Synoptic Answer Key | — | 6 | Open |
| Re-Examination — Question Paper | 06 Feb 2026 | 7 | Open |
| Re-Examination — Synoptic Answer Key | — | 6 | Open |
Both papers carry 50 marks over 2 hours, with Q1 compulsory and any 4 of Q2–Q7 to be attempted. Both include a z-table and a t-table as their last pages.
Course documents and other material
Prescribed vs actual textbook — worth knowing
The syllabus lists as its Text Book: U. Dinesh Kumar, "Business Analytics — The Science of Data-Driven Decision Making", 2nd edition, Wiley India 2022 Syllabus p. 2. That book was not supplied and is not on this site.
The book that was supplied is the first Reference Book: Levin, Rubin, Siddiqui & Rastogi, Statistics for Management, 8e. And the evidence says this is the one the course actually runs on — the worked examples in your class notes are Levin's problems (the Georgia hospital stay, the plant manager's coal usage, the $19,000 bank employees), and the Sampling Distribution deck follows Levin's chapter structure and notation exactly.
Everything on this site is cited to Levin. If a question in the exam uses notation you do not recognise, it is more likely to come from a deck than from a textbook you were never given.
Discrepancies, gaps and errors found
Five things that do not line up. Each is flagged where it matters rather than silently smoothed over.
The key writes: "P(−1.20 < z < 1.20) = 0.7698 − 0.1151 = 0.6547" Key p. 1.
The first figure should be 0.8849, which is Φ(1.20). The correct line is 0.8849 − 0.1151 = 0.7698 — the answer that was mistakenly typed into the first position and then subtracted from.
Two independent checks confirm 0.7698: the Re-Exam's structurally identical question is worked correctly (0.9625 − 0.0375 = 0.9250), and in your class's 0-to-z table, 2 × A(1.20) = 2 × 0.3849 = 0.7698. Write 0.7698. Full working →
Your class notes write the rule of thumb as n/N < 0.5 Class notes p. 5, p. 6. The Sampling Distribution deck says 0.05 slide 21, and so does Levin §6.7 p. 302.
Almost certainly a dropped zero while copying. Use 0.05 — it is the standard convention and it is what two of your three sources say. In practice it rarely bites: if an exam question gives you N at all, it usually intends the correction to be applied. The Final's Q4 (a) has n/N = 0.04, below either threshold, and the official key applies the FPC anyway Key p. 4. Safest rule: if N is given, use the FPM and state the sampling fraction.
Page 4 of the probability-distribution notes lists "For Poisson: Mean = np" and "For Binomial: Mean = λ, SD = √λ" Class notes p. 4. The labels are the wrong way round.
Confirmed by the deck slide 25 and slide 31, and by Levin Ch. 5. The correct version is used throughout this site.
The table supplied to your class — Standard Normal table.jpg, "Areas of the Standard Normal Distribution" — gives A(z), the area between 0 and z, with entries running to 0.4998. Your class notes use it throughout: z = 1.58 → .4429, z = 2.05 → .4798.
The official answer keys use the cumulative table, Φ(z), with entries running to 1.0000: Φ(1.20) = 0.8849, Φ(−0.4) = 0.3446 Key p. 2.
Both reach the same answers; only the intermediate arithmetic differs, related by Φ(z) = 0.5 + A(z). This site works everything in the A(z) convention your class uses and quotes the key's cumulative figures alongside. Both tables and the conversion rules →
The syllabus puts "Determination of Sample Size" in Unit 7, and gives Unit 6 only "Importance of Sample size" Syllabus p. 2. The deck that teaches it is titled "Unit 6 (Part II) — Determination of Sample Size" slide 1.
It is taught as Unit 6, so it is covered here as Unit 6 Concept 5. Both past papers asked it in the Q3 (b) slot, so the ten minutes it takes to learn are worth spending even if your mid-term turns out to define the boundary strictly.
What is deliberately not here
- Units 7–14. Interval estimates, the t-distribution, hypothesis testing, two-sample tests, the F test, ANOVA and the chi-square test are all in the syllabus but belong to the Term End Examination. Nothing has been written for them. Note that the Sampling Dist deck's slides 24–43 do continue into estimation and the t-distribution — those slides exist in the viewer, but no notes here explain them.
- The prescribed textbook (Dinesh Kumar). Not supplied, so not cited.
- SPSS. The syllabus names "SPSS functions" for Unit 4 Syllabus p. 1, but no SPSS material was supplied and neither paper referenced it. Only the Excel functions, which the decks do show, are documented.
- A past mid-term paper. None was supplied. The two papers on this site are end-term papers, and the "seven recurring shapes" they reveal are evidence of how this department writes questions — not a guarantee of your mid-term's structure.
- Video timestamps. Reading a video's chapter markers requires loading the video page, which was not possible from the environment this site was built in. Rather than print plausible-looking timestamps, none are given.
How to rebuild or extend this site
Two scripts regenerate everything derived. Both are idempotent — already-rendered pages are skipped, so re-running is cheap.
cd BS/StudySite python3 scripts/render_sources.py # decks → PDF → page images python3 scripts/gen_manifest.py # rescan assets/sources/ → js/sources.js python3 scripts/make_figures.py # crop individual exam questions
To add a source: put its id in PDFS or DECKS in render_sources.py, add a matching entry to META in gen_manifest.py, run both, then cite it with a src-ref anchor carrying data-src set to your id and data-page (or data-slide) set to the locator.
Requires pdftoppm and pdfinfo (poppler), soffice (LibreOffice, for the .pptx decks) and Python's Pillow. The site itself has no build step and works offline from the file system — the originals in the BS folder are never modified.
| Key | Does |
|---|---|
| / | Focus the search box |
| [ | Show or hide the sidebar |
| ← → | Page through the open source document |
| Esc | Close the source viewer or the search results |
The source panel can be dragged wider by its left edge, and the width is remembered. So is your light/dark choice, shared across all four subject sites.