In this course the participants will learn how to use R for simple tasks such as data loading, cleaning, transformation and aggregation, simple statistical analysis, as well as plotting. Furthermore, the installation of packages, generation of reports, and a brief outlook towards implementing custom functions will be taught.
The programming language R is by far one of the most popular tools for statistics and data science. It is used by many scientists from different fields, including mathematics, physics, chemistry and biology. Two of the reasons for its popularity are first its simplicity compared to other programming languages and second its remarkably large repositories of packages, such as CRAN and Bioconductor that extend its functionality beyond what is available in the base version.
While the participants will not be able to implement dedicated R packages after the course, they will have a feeling on what is possible for them, and be capable of implementing R scripts on their own, which shall help them evaluate their datasets independently. Furthermore, with these basic knowledge about R the participants should also be equipped with enough knowledge about the R ecosystem to search for respective packages themselves or even dwell further into literature and extend their R knowledge themselves.
Target group: Students who have no or little experience in programming and who want to utilize methods outside of Microsoft Excel for their data analysis.
Prerequisites: None
Evaluation: Participation
Teaching format: Presentations and hands-on exercises.
ECTS: 2 Year: 2023
Track segment(s):
Service
Teacher(s):
Christoph Büschl Christian Jansen
Teaching assistant(s):
If you want to enroll to this course, please click: REGISTER
- Teacher: Christoph Büschl
- Teacher: Christian Jansen