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R Basics – Statistical Data Analysis


24. May 2024 09:00 – 24. May 2024 17:00
25. May 2024 09:00 – 25. May 2024 17:00
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Philipps-Universität Marburg, MARA, F|05, Deutschhausstraße 11+13, Seminar room 01.0010

R has become one of the most popular programming language in statistics and data science, with millions of R users worldwide in academia and beyond.

Begin your journey to learn R with us in this two days training. With help of many hands-on coding examples and a close mentoring by two experienced trainers, you will master the basic usage of R enabling you to solve your own data analytics challenges.

Intended Learning Outcomes

  • You will understand the statistical programming workflow and basic syntax of R as well as the usage of RStudio as development environment.
  • You will know how to read and process different data sets by learning the basic R data structures and the powerful extension package dplyr.
  • You will be able to create visualizations from command line, using base R as well as ggplot2.
  • You will understand how to apply common statistical tests and models, such as t-test, regression, ANOVA, and interpret the R outcome.
  • You will be aware of AI tools that help you with coding and debugging.
  • You will gain an overview on how to automatize your workflows and make your research reproducible.

Didactic Methods

Trainer input, hands-on coding exercises, close mentoring by trainers


You are requested to bring your own laptop with R and RStudio pre-installed. Both tools are open source and can be downloaded for free from the internet.

Proficiency in English at the B2 level of competency is required.


May 24, 2024, 9 am–5 pm, and
May 25, 2024, 9 am–5 pm

Target group

Doctoral candidates from all disciplines


Maximum number of 10 participants
Internal 50 EUR
External 150 EUR


Please register until May 10, 2024 using the online registration form.


Dr. Matthias Duschl
Dr. Daniel Lee

Event Organizer

MArburg University Research Academy (MARA)
Doctoral Program for Life and Natural Sciences