GESIS Training Courses

Scientific Coordination

Sebastian E. Wenz
Tel: +49 221 47694-159

Administrative Coordination

Jacqueline Schüller
Tel: +49 0221 47694-160

Short Course A: Introduction to R for Data Analysis

Cologne/Unter Sachsenhausen 6-8
Course Duration
Wed-Th: 10:00-13:00 | 14:00-17:00 CEST
General Topics:
Course Level:
Software used:
Students: 220 €
Academics: 330 €
Commercial: 660 €
Additional links
Lecturer(s): Jan Schwalbach, Dennis Abel

About the lecturer - Jan Schwalbach

About the lecturer - Dennis Abel

Course description

The open-source software package R is free of charge and offers a variety of standard data analysis procedures as well as a comprehensive repertoire of highly specialized processes and procedures, even for complex applications. After introducing the basic concepts and functionalities of R, we will go through a prototypical data analysis workflow in the course: import, wrangling, exploration, (basic) analysis, reporting.
The full syllabus of the course including the day-to-day schedule will be published here in April.

Target group

You will find the course useful if you want to use R to wrangle, explore, visualize, and analyze your data.

Learning objectives

By the end of the course, you should be:
  • comfortable with using R and RStudio,
  • able to import, wrangle, and explore your data with R,
  • able to conduct basic visualizations and analyses of your data with R.
Organizational structure of the course
The best way to learn R is to try things out and apply the presented concepts. Therefore, we will have a mixture of lectures and hands-on exercises. More specifically, each topic will be introduced in a lecture by the instructors. You will then receive a set of exercises on each topic that you work on alone. The solution of the exercises will be discussed before the start of the next lecture part.


  • Prior experience with quantitative data analysis, basic statistics, and regression is needed.
  • Experience with using other statistical packages (e.g., SPSS or Stata) is helpful, but not a requirement.
Software and hardware requirements
You will need to bring a laptop computer to successfully participate in this course.
You should install R ( and RStudio ( before the start of the course. Both programs are free and open source.