This two-day course provides an introduction to the fundamental concepts and methods of statistics with a strong focus on practical application and interpretation. Participants will learn how to describe and visualize data, understand probability and statistical modeling, estimate parameters, construct confidence intervals, and perform hypothesis testing.
The course begins with the foundations of statistical thinking, including random variables and probability distributions, before introducing standard statistical tools commonly used in scientific research. Participants will gain an understanding of parameter estimation and its properties, confidence intervals, hypothesis testing, and frequently occurring testing problems.
On the second day, the focus shifts to regression analysis. Topics include simple linear regression, multiple regression models, assumptions and diagnostics, prediction, and the interpretation of R output. The course will also provide a brief introduction to more advanced methods, including principal component analysis (PCA), decision trees as a machine learning prediction tool, and writing professional statistical reports with Quarto.
The course is designed for beginners and aims to make participants feel comfortable working with statistical methods and interpreting statistical results. No specific prior knowledge is required.
Throughout the course, participants will work with the statistical programming language R. Participants are asked to bring a laptop with the latest versions of R and RStudio installed. A useful introduction to R can be found at https://r4ds.hadley.nz/.
Participants are also welcome to submit statistical questions or datasets from their own research projects to the instructor no later than two weeks before the course. Depending on the available time, selected examples may be incorporated into the course.
Instructor: Dr. Lennart Oelschläger
Location: Schlossplatz 4, Room 107
Schedule:
Monday: 09:00–12:00 and 13:00–16:00
Tuesday: 09:00–12:00 and 13:00–16:00
Registration closed