Lecturer: Mag. Thomas Forstner
Course number: 366.554
Statistics course with focus on various univariate parametric and non parametric test problems and the application of R to solve these test problems.
Students understand advanced methods of inductive statistics with focus on parametric and non-parametric statistical test procedures. They can analyze data using these methods and can interpret statistical methods and results in other work. They can also perform these statistical analyses using the program package R.
- parametric statistical tests for continuous data (one-sample t-test, two-sample-test, paired t-test)
- sample size estimation and power-analysis for the t-test family
- non-parametric statistical tests for continuous and/or rank data (Kolmogorov-Smirnov test, Mann-Whitney-U test, Wilcoxon test)
- tests for categorical data (binomial test, chi-square test, Fisher's exact test, McNemar's test)
- summarizing the results of a binary classification system (sensitivity, specifity, ROC curves, ...)
- odds-ratio and risk-ratio (interpretation/tests)
- summary statistics for association/correlation (Cramer's V, correlation coefficient, partial correlation coefficient) and corresponding statistical tests
- introduction into analysis of variance