GESIS Training Courses

Scientific Coordination

Verena Kunz

Administrative Coordination

Claudia O'Donovan-Bellante
Tel: +49 621 1246-221

Introduction to R

Online via Zoom
General Topics:
Course Level:
Software used:
Students: 300 €
Academics: 450 €
Commercial: 900 €
Additional links
Lecturer(s): Natalia Umansky, Christian Pipal

About the lecturer - Natalia Umansky

About the lecturer - Christian Pipal

Course description

R is a software environment for statistical computing that is both powerful and versatile, as well as open source. It allows users to manage and manipulate data, conduct a wide range of statistical analyses, and present scientific results in various forms. However, for individuals who are new to R, the experience can be challenging as it is a programming language that operates differently from commercial statistical software packages like SPSS or Excel that primarily use graphical user interfaces.
This three-day workshop addresses researchers who have little to no prior experience with R. During this time, we will start by introducing R and the popular development environment RStudio. We will move at a slow pace, explaining the fundamental concepts of R usage, including basic programming concepts and how to use RStudio. Additionally, we will show participants how to extend R's capabilities to perform analyses using R packages. We will also cover the popular R package "tidyverse", which is useful for performing common data wrangling tasks, such as reading-in, sub-setting, and transforming data from various sources. Finally, we will use the "tidyverse" package to conduct basic exploratory data analysis and visualizations.
Throughout the workshop, participants will complete exercises that will provide them with reference material for common R programming tasks. We will also emphasize the use of online resources to help participants find answers to programming problems. By the end of the course, participants will have a solid understanding of the fundamentals of R, including how to work with tabular data, such as reading in, transforming, and analyzing data. Our goal is to equip participants with all the tools and resources they need to continue advancing their R skills on their own.

Target group

Participants will find the course useful if:
  • they are new to the R language.
  • they want to get a practical introduction to R and RStudio.
  • they want to use R to import, manage, transform, explore, analyze, and visualize data.
  • they would like to learn R in an open and cooperative environment, where questions and explicitly encouraged.

  • Learning objectives

    By the end of the course participants will:
  • be familiar with setting up and using R and RStudio on their computer.
  • have a basic understanding of fundamental programming concepts and their application in R.
  • be able to perform basic data wrangling tasks using the “tidyverse”.
  • be able to visualize data using “ggplot2”.
  • be able to interpret error messages and find answers online.
    Organizational structure of the course
    The course's structure aims to equip participants with ample resources to acquaint themselves with the R environment. The workshop is interactive and incorporates brief lectures on various topics, followed by corresponding practical lab sessions. Instructors will introduce each topic briefly and then assign a set of exercises to the participants. These solutions will be discussed in class before the start of the next input session. During the seminar, both instructors will be on hand to provide guidance and practical advice to the participants.


  • A basic understanding of quantitative social science and hypothesis testing, including introductory statistics (e.g., distributions, t-tests, cross tables, and linear regression).  
    Software requirements
    Participants will be requested to download R and RStudio in advance. However, a detailed instruction will be
    sent beforehand via e-mail, and there will be points of contact available for troubleshooting.


    Recommended readings