About the Course

S Modern Applied Regression Analysis with R

The seminar deals with regression techniques for cross-sectional and longitudinal data. Different methods are implemented with the statistical programming language R and illustrated by using empirical data examples.

R is a free open source software for data analysis, which is widely used in academic research and business applications. R and RStudio are available free of charge for all major operating systems.

The course is divided into the following topics:

- Introduction

- Non-parametric regression methods and scatterplot smoothing

- Parametric regression methods (OLS)

- Mediation analysis and interaction effects

- Semiparametric regression and splines

- Generalized linear models and logistic regression

- Reporting and visualizing regression results

- Panel regression: fixed-effects and random-effects models

- Regression in machine learning applications: feature selection and cross validation

The seminar follows a flipped-classroom approach. Participants have access to extensive interactive tutorials that introduce and explain various regression techniques and their implementation in R. The seminar sessions provide the opportunity to deepen the topics covered, ask questions, and discuss example analyses using R.

Voraussetzungen für Studiennachweise / Modulprüfungen

Attendance certificates (“Studiennachweis”) can be obtained through active participation and the completion of exercises. The module examination additionally includes the preparation of a term paper.

Lehrende

Sebastian Gerhartz

Termine

• Monday, 13.04.2026 (1. Termin)
  10:00 bis 12:00 Uhr
  GD E2/208 CIP-Pool

Anmeldung

Bitte melden Sie sich in eCampus für die Veranstaltung an.