Detailed information 
Original study plan 
Master's programme Computer Science 2021S 
Objectives 
Students understand advanced methods of inductive statistics with focus on parametric and nonparametric 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.

Subject 
 parametric statistical tests for continuous data (onesample ttest, twosampletest, paired ttest)
 sample size estimation and poweranalysis for the ttest family
 nonparametric statistical tests for continuous and/or rank data (KolmogorovSmirnov test, MannWhitneyU test, Wilcoxon test)
 tests for categorical data (binomial test, chisquare test, Fisher's exact test, McNemar's test)
 summarizing the results of a binary classification system (sensitivity, specifity, ROC curves, ...)
 oddsratio and riskratio (interpretation/tests)
 summary statistics for association/correlation (Cramer's V, correlation coefficient, partial correlation coefficient) and corresponding statistical tests
 introduction into analysis of variance
 introduction into R

Criteria for evaluation 
 short weekly homework assignments
 exam at the end of semester
 each part is weighted with 50% regarding the final grade

Methods 
 lecture by instructor
 weekly homework assignments and presentation/discussion of these assignments
 livecoding in R

Language 
German/English 
Study material 
slides provided by instructor, available in Moodle

Changing subject? 
No 
Further information 
department homepage: www.systat.jku.at
continuative courses:
 Special Topics: Biostatistics in Clinical Research (introduction into biostatistics)
 Special Topics: Applied Biostatistics (seminar about biostatistics)
 Special Topics: Statistics 3  Univariate Methods
 Special Topics: Statistics 4  Multivariate Methods
 Special Topics: Statistical Coaching (support for statistical aspects regarding bachelor thesis, master thesis, ...)
