Students become familiar with the basic methods of inductive statistics and extend their knowledge of the use of statistical software. They thus acquire the ability to understand and verify statistical statements. Students know basic statistical methods. They can use simple quality standards to choose one of several methods.

None

This lecture provides students with an overview of the most important methods of statistical testing. The following topics are covered: statistical hypothesis testing, type I and II errors, level of significance, parametric and nonparametric methods, t-test, test of normality, Mann-Whitney U test, ANOVA, Kruskal-Wallis test, Chi-squared test.

• Bühl A. (2016): SPSS 23: Einführung in die moderne Datenanalyze. 15th rev. ed. Pearson Studium.
  
• Bortz J./ Schuster C. (2010): Statistik für Human- und Sozialwissenschaftler: Limitierte Sonderausgabe. 7th ed. Springer.

Lecture, tutorial

Module exam (see module description for details).