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Pharmaceutical Biostatistics
Last Updated: 2026-06-03 00:14:39
Abstract
The course conveys skills necessary to understand, plan, and conduct statistical analyses. This includes a short recapitulation of statistical basics and extends to statistical methods applied in Industry. The student can apply their knowledge to practical examples using the statistical software R and R Studio.
Objective
Know the most frequently used statistics of exploratory data analysis (EDA) and be able to derive these from real data. Know how to create important graphical visualizations in R how to explore data. Understand concepts of probability theory and statistics, including point estimation, statistical tests, interval estimation, and sample size calculation. Understand the origin of multiplicity issues and its avoidance. Understand, and apply different statistical methods, such as ANOVA, linear regressions with the statistical software R. Explain their assumptions and limitations, and be able to run theses analyses in R including diagnostic checks based on real data. Be able to plan, analyze experiments, and be able to interpret results of respective statistical analyses. Large language models (LLM) will be used to guide R coding.
Content
Exploratory Data Analysis (EDA) Probability & Statistics ANOVA & linear regression Methods to adjust for multiplicity
Resources
Lecture Notes
Presentations (pdf or similar format) will be sent to students prior to course.R scripts will be shared after each course day.
Literature
As a preparation for the course, please, review your basic statistic course or use books that were recommended during your basic statistic course (e.g. Stahel, W. 2008, Statistische Datenanalyse, Eine Einführung für Naturwissenschaftler, Springer Vieweg Verlag or other basic text books). It is expected that the student has an understanding of basic statistical concepts.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
- Digital
- The examination takes place on your own device. No installation of SEB required.
Registration & Places
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Pharmaceutical Biostatistics
Block course (see special program)
Room HCP E47.2
|
No time listed | 24 h semesterly |