Students learn to operate R, to perform data manipulation and visualisation, work with the (generalized) linear models, conduct simulation studies (e.g. bootstrap) and present results of data analyses in publication ready tables and figures. We will work with the RStudio environment and R Markdown. The focus will be on the tidyverse package.

R is a very popular and powerful platform for data manipulation, visualization, and analysis and has a number of advantages over other statistical software packages. A wide community of users contribute to R, resulting in broad coverage of statistical procedures, including many that are not available in any other statistical programme.

This course is intended for applied researchers and (master) students who already use statistical software and would like to learn to use, or improve their usage of, the R environment. Understanding basic statistical theory such as t-tests, hypothesis testing, and regression is required. No previous experience with R is required. For participants who already have some experience with R, we offer more challenging exercises.

Data Science specialisation
This course can be taken separately, but is also part of a series of 8 courses in the Summer School Data Science specialisation taught by UU’s department of Methodology & Statistics:

1. Data Science: Programming with Python (Course code S17, 7-11 July 2025)
2. Data Science: Network Science (Course code S37, 7-11 July 2025)
3. Data Science: Statistical Programming with R (this course)
4. Data Science: Applied Text Mining (Course code S42, 14-18 July 2025)
5. Data Science: Machine Learning with Python (Course code S70, 21-25 July 2025)
6. Data Science: Advanced Techniques for Handling Missing Data (Course code S28, 2026)
7. Data Science: Data Analysis (Course code S31, 2026)
8. Data Science: Text Mining with R (Course code S41,2026)