Welcome! If you are here you are mostly likely attending the DEPICT workshop Bootcamp 15. april 2026 in Bergen, Norway. Please read through this page to prepare yourself for this part of the bootcamp. If you wish you may skip directly to the required files for the session, it won't hurt my feelings (too much).
Why R and RStudio?
Linguistics is undergoing a quantitative sea change. Since Baayen’s landmark textbook Analyzing Linguistic Data (2008), language data is increasingly more accessible, and the means to analyze it, increasingly more sophisticated. Statistical competence in a wide range of techniques and in evaluating claims based on diverse methods is more necessary than ever, for linguists of all disciplines. This quantitative wave is closely followed by the push for open and reproducible science.
We will rely on R, an open-source statistical programming language widely used by practitioners in many different fields, both inside and outside academia. Although it is possible to work directly in R, using an integrated development environment such as RStudio makes things much easier. RStudio integrates a text editor with the R console, so you can write, run, and see the results of your analyses more easily.
We will download and install both R and RStudio to your computer. Here is a link to access them (the version you install depends on whether you are using Windows or Mac).
RStudio Interface
Once you have downloaded and installed both R and RStudio, you will be confronted with this interface.
Beyond the various menus at the top, the interface is split into four panels. We will use the upper-left panel to write the code that instructs R to run the analyses, which means you need to open a new R Markdown (from the menu or clicking the icon). While it is also possible to directly type the commands in the console, using R Markdown enables saving, replicating, and sharing your work later on. Most of the results will show up in the console in the lower-left panel, and the tab plots in the lower-right panel reproduces the visualisations we implement. (The tab files shows the structure of the directory where we are working.) Lastly, the environment, located in the upper-right panel displays the objects that we load into the system.
Tutorial data to download
Download and upzip this archive for all files you will need in the bootcamp session "Sign Language Analysis with R".
