The objective of the course is to provide basic skills for graphically presenting data in a scientific context (article or presentation). You will learn R programming basics, creating data report quickly and effectively with R Markdown, importing, cleaning and organizing data (tidy data), as well as basic and more advanced plotting (grammar of graphics). The module consists of short talks followed by exercises. Moreover, you will apply your knowledge on your own data which you will present in a 10-minute presentation on the last day. The aim is that you are coming to the course with draft figures for a paper in the making, and will end up with improved figures and a workflow to generate them.
Participants must join the lecture with their own laptop, with R studio installed.
The first lecture gives basics in R. It is optional. You can skip it if
- you can do all TODOs of this short intro to R by Paul Torfs & Claudia Brauer: cran.r-project.org/doc/contrib/Torfs+Brauer-Short-R-Intro.pdf
- and if you’re able to compute in R the number of women who survived the Titanic from the comma-separated flat file available at: www.gagneurlab.in.tum.de/fileadmin/w00bxk/www/dataset/titanic.csv
Recommended reading
R for Data science, by Garrett Grolemund and Hadley Wickham
- Dozent: Ziga Avsec
- Dozent: Jun Cheng
- Dozent: Linus Dietz
- Dozent: Julien Gagneur
- Dozent: Christian Mertes