Educational repository with R implementations of core Mathematical Statistics concepts,
designed for undergraduate students in Data Analysis. Covers hypothesis testing, confidence
intervals, ANOVA, normality tests, Pareto optimization, and applied statistical methods.
This repository contains workshop materials for the Mathematical Statistics module
of the Data Analysis course (Spring Semester). Materials include:
- Seminar sessions with practical R exercises
- Test and exam examples with solutions
- Applied projects (Pareto optimization, portfolio analysis)
📖 Supplementary materials:
- Course website — presentations, formulas, examples
- Bilingual Glossary
- Statistical tests cheat-sheets
- Books, manuals & external resources
| Folder | Contents |
|---|---|
seminars/ |
Seminar sessions: interval estimation, ANOVA, hypothesis testing |
tests/ |
Test and exam variants with solutions (anonymized) |
code/ |
R cheat-sheets: normality tests, hypothesis testing, confidence intervals, Pareto optimization |
glossary/ |
Bilingual glossary of mathematical statistics terms |
resources/ |
Books, manuals, creative topics, tool links |
| # | Topic |
|---|---|
| 19 | Interval Estimations — Part 1 |
| 20 | Interval Estimations — Part 2 |
| 20 | ANOVA |
| 21 | Hypothesis testing - Part 1 mean |
| 22 | Hypothesis testing - Part 2 variance |
| 25 | Hypothesis testing - Part 3 proportion |
# Example: One-sample t-test
x <- c(18.2, 13.7, 15.9, 17.4, 21.8, 16.6, 12.3, 18.8, 16.2)
t.test(x, mu = 16, conf.level = 0.95)- R — statistical computing and graphics
- Base R & packages (BSDA, confintr, DescTools, rPref, nortest, sm)
- Excel — Data Analysis ToolPak
- GitKraken — version control
These materials support the Data Analysis course.
The course combines theoretical foundations with hands-on R programming and Excel tools.
🔗 External resources:
- Course site with presentations
- Probability & Statistics Glossary — bilingual terms (EN/RU)
- R Code Reference — distributions, Excel functions, portfolio formulas
For questions about the course materials, please reach out via GitHub Issues
or visit vladova.ru.