Syllabus
1. Basic concepts of mathematical statistics, principles of testing hypotheses.
2. Testing hypotheses concerning the mean - t-tests (one-sample, two-samples, paired) and their non-parametric alternatives.
3. Analysis of variance - one-way and two-way ANOVA.
4. Correlation, linear regression, independence testing in contingency tables.
5. Multivariate statistics (cluster analysis, principal components, discimination analysis).
Annotation
Selected principles of statistical inference. The analysis of real data on computer using an appropriate statistical software is an important part of the course.
The attention is devoted to correlation and regression models, analysis of variance, some algorithms of cluster analysis and fundamentals of time series analysis.