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Table of Contents

Lectures and Tutorials

Lectures

L Date Lecturer Contents Materials
1 23.9. JK Introduction, course map, review of the basic stat terms/methods. SAN_intro, Skulls
2 30.9. JK Multivariate regression (continuous dependent variable, linear regression, p-values, overfitting). SAN_regression
3 7.10. JK Multivariate regression (non-linear models, polynomial and local regression). SAN_nlin_regression
4 14.10. JK Multivariate confirmation analysis (ANOVA and MANOVA). SAN_manova
5 21.10. JK Multivariate confirmation analysis (ANOVA and MANOVA). see the previous slides
6 28.10. Public holiday
7 4.11. JK Discriminant analysis (categorical dependent variable, LDA, logistic regression). SAN_discriminant
8 11.11. JK Dimension reduction (PCA and kernel PCA). SAN_dimred
9 18.11. JK Dimension reduction (other non-linear methods). see the previous slides
10 25.11. TP Robust statistics. SAN_robust
11 2.12. TP Anomaly detection. Anomaly
12 9.12. ZM Empirical studies, their design and evaluation. Power analysis. SAN_emp_studies_power_analysis
13 16.12. JK Clustering (formalism, k-means, EM GMM, hierarchical). SAN_clustering
14 6.1. JK Clustering (spectral clustering). SAN_spect_clustering

Tutorials

T Date Teacher Contents Materials
1 23.9. AVL Programming in R, introduction, libraries including learning package Swirl. Lab1
2 30.9. AVL Basic statistics in R, prerequisities, data visualization in R. Lab2
3 7.10. JB Multivariate linear regression Lab3
4 14.10. JB Multivariate non-linear regression nonlinear_wage_tutorial.zip assignment1_2019.zip nonlinear_wage.zip
5 21.10. JB Multivariate confirmation analysis tutorial_anova.zip assignment2.zip
6 28.10. Public holiday
7 4.11. JB Discriminant analysis lda_tutorial.zip assignment3_lda.zipLDA derivation for Dimensionality reduction
8 11.11. JB, AVL Mid-term test datasets.zip
9 18.11. AVL Dimension reduction DimRed, assignment4-dimred.zip
10 25.11. TP Robust statistics instruction.pdf
11 2.12. TP Anomaly detection – assignment. anomaly2.pdf anomaly-problems.zip
12 9.12. ZM Empirical study design, power analysis empirical_study
13 16.12. Consultations for the final assignment clustering_intro.zip
14 6.1. AVL Clustering advanced_clustering.zip, spect_clust.pdf
courses/b4m36san/content.txt · Last modified: 2020/01/08 15:27 by klema