1. Introduction to probability theory
2. Discrete Random Variable
3. Continous Random Variable
4. Data - description and visualization
5. Sample statistics, Introduction to Theory of Estimation
6. Hypothesis testing (principle, factors influencing the strength of the test)
7. One sample tests (t-test, scatter test, Wilcoxon test, binomial split test)
8. Two sample tests (pair tests, two-sampling t-test, scattering compliance test, Mann-Whitney test, binomial partition test)
9. ANOVA, Kruskal - Wallis test
10. Goodness of Fit Tests
11. Analysis of independence in contingency tables
12. Introduction to Regression Analysis (I.)
13. Introduction to Regression analysis (II.)