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.)
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.)