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.

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

By the end of the course, you should be:

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.

  

You will need to bring a laptop computer to successfully participate in this course.

You should install R (https://cran.r-project.org/) and RStudio (https://posit.co/download/rstudio-desktop/) before the start of the course. Both programs are free and open source.