Welcome to the course “Data Analysis with R” that will be held twice a year at the Faculty of Social Sciences at the Vrije Universiteit Amsterdam. In order to facilitate the switch to R in our faculty, we organize four monthly, informal sessions in which the basics of using R for statistical analyses will be introduced, discussed and practiced. The course is consecutive, that is each session builds on the previous one.
The course is organized collaboratively by various colleagues from the faculty of social sciences. Everybody is welcome to join at any time. Below, you’ll find an overview of the planned sessions in the summer semester 2022.
In each session, you will perform analyses on your own computer. So please bring your own laptop and make sure that you have Internet access.
Before the first session, we ask you to make sure that R and RStudio is installed on your computer and that you have played around with R at least a little bit. For this purpose, we invite you to work through the first tutorial called “Getting Started”. But don’t worry if something doesn’t work. The basics of using R will again be covered in the first session.
| # | Date | Room & Time | Topic | Material | Teacher |
|---|---|---|---|---|---|
| 1 | 21-04-2022 | HG-11A24 (15.30-17.00) | Introduction to R and RStudio | R Basics | Kasper Welbers |
| 2 | 19-05-2022 | HG-11A24 (15.30-17.00) | Data Wrangling and Transforming | Transforming & summarizing data | Philipp Masur |
| 3 | 02-06-2022 | HG-11A24 (15.30-17.00) | Data Visualization | Basics of data visualization with ggplot2 | Nicolas Mattis |
| 4 | 16-06-2022 | HG-10A20 (15.30-17.00) | Basic statistics: t-tests, analysis of variance, and regression models | Statistical modeling in R | Joris Melchior Schröder |
Learning R of course doesn’t end after these four sessions. We hope that afterwards, you will want to dive deeper into the many different things that one can do with R. For this purpose, we created various tutorials that can help you learn more advanced methods (e.g., multilevel modeling, structural equation modeling, machine learning, text analysis, etc.). You can find the handouts (similar to the ones we use in this course) and corresponding video tutorials on this repository: https://github.com/ccs-amsterdam/r-course-material
We strongly recommend to also work with other tutorials and handbooks, which cover different aspects of using R. Below is a short list of books that we found useful:
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Field, A., Miles, K., & Field, Z. (2012). Discovering statistics using R. Sage.
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van Atteveldt, W., Trilling, D. & Calderon, C. A. (2022). Computational Analysis of Communication. Wily-Blackwell. Open access version: https://cssbook.net/