L | Date | Lecturer | Contents | Materials |
1 | 21.9. | JK | Introduction, course map, review of the basic stat terms/methods. | SAN_intro, Skulls |
2 | 28.9. | | Public holiday | |
3 | 5.10. | JK | Linear regression (continuous dependent variable, simple linear regression, p-values). | SAN_regression |
4 | 12.10. | JK | Multivariate regression (overfitting, model shrinkage). | see the previous slides |
5 | 19.10. | JK | Nonlinear regression (polynomial regression, splines, local regression). | SAN_nlin_regression |
6 | 26.10. | JK | Multivariate confirmation analysis (ANOVA and MANOVA). | SAN_manova |
7 | 2.11. | JK | Discriminant analysis (categorical dependent variable, LDA, logistic regression). | SAN_discriminant |
8 | 9.11. | JK | Dimension reduction (PCA and kernel PCA). | SAN_dimred |
9 | 16.11. | JK | Dimension reduction (other non-linear methods). | see the previous slides |
10 | 23.11. | TP | Robust statistics. | SAN_robust |
11 | 30.11. | ZM | Empirical studies, their design and evaluation. Power analysis. | SAN_emp_studies_power_analysis |
12 | 7.12. | TP | Anomaly detection. | Anomaly |
13 | 14.12. | JK | Clustering (formalism, k-means, EM GMM, hierarchical). | SAN_clustering |
14 | 4.1. | JK | Clustering (spectral clustering). | SAN_spect_clustering |