Online Workshop: Introduction to R (EN)

Kursbereich 3: »Wissenschaftliche Methoden«

Target Group

PhD students and postdoctoral researchers of all research areas

This introductory course is intended for participants with no or little prior knowledge of R or statistics and serves as a starting point for further work with R as well as for the following course "Statistical Methods with R".

The open-source programming language R is one of the best solutions for data analysis, data mining and predictive analytics. Participants will learn that R has become a widely used tool for all tasks related to data management and statistics. 

Aim of the course 

The aim of the course is to teach the basic functionalities, logic and terminology of the programming language R and to lay – with the help of practical tips and exercises – the foundation for independent work with R. 


  • First steps into R: the program R, CRAN-Mirror, different environments/editors of R, use of the internal help functions, help on the internet 
  • Concept and philosophy of R: the programming language, objects, value assignments, functions 
  • Data structures and their properties: vectors, dataframes, lists, etc. 
  • Importing data: TXT, CSV, XLS and SAV files, Internet sources, etc. 
  • Data management: creation of new variables, conditional recoding, simple calculations, missing values 
  • dplyr, tidyr and handling of special data types 
  • Statistical key figures, simple tables and graphs 
  • First simple statistical calculations 
  • Loops and control elements 
  • Data visualization 
  • Introduction to the leading IDE RStudio

Trainer - Christoph Schmidt (eoda GmbH)

Christoph Schmidt has been working as a Data Scientist at eoda GmbH since 2017, primarily on projects containing machine learning or forecasting tasks. In addition to that, he teaches courses such as Machine Learning with R or Time Series Analysis with R.


  • 2 July 2024, 09:00 – 17:00 h (incl. lunch break)
  • 3 July 2024, 09:00 – 17:00 h (incl. lunch break)
  • 4 July 2024, 09:00 – 17:00 h (incl. lunch break)


Please register via the »Graduates Virtual Campus«:

Eine Woche vor Kursbeginn erhalten Sie den Einwahl-Link für die Veranstaltung. Melden Sie sich über das GRS-Kursportal an.


Robert Rode
ZE Graduate Research School (GRS)
T +49 (0) 355 69-3479