Statistik für Biowissenschaftler / Statistics for Life Scientists

This hands-on workshop offers an introduction to statistical data analysis. Following an introduction to fundamental concepts, key metrics and appropriate forms of data visualization are addressed within the framework of univariate and bivariate statistics. Building on this, the basic principles of statistical hypothesis testing are introduced in the context of inferential statistics. Within the framework of modeling relationships, particularly of quantitative or categorical outcomes across multiple samples, the focus is initially on commonly applied tests, e.g., t Test, MWU-test, ANOVA, Chi-Squared test, Fisher’s Exact test, and more. Subsequently, correlation and regression analyses are presented. This section highlights simple and multiple linear regression, logistic regression and Cox regression. In addition, more advanced statistical modeling techniques are introduced, in particular mixed models for analyzing dependent structured data, e.g. clustered, repeated-measures or longitudinal data. Finally, the essential biometric considerations in animal research projects, including, among others, study design and sample size planning within the 3Rs (core: Reduction), are presented. The acquired knowledge is independently reinforced through exercises and subsequently discussed and interpreted collectively. No prior programming experience is required.

The workshop consists of 5 instructional units, the content of which builds on one another. Attendance in all course components is required for the awarding of credit points.

Course language: German or English as required