In order to fully participate in this course, you should bring a laptop to work on during the sessions and make sure you have the following installed on it before the first session.

• R, version 4.1 or later. You can install this from the University’s Company Portal software repository. Alternatively, visit https://cran.rstudio.com, or adopt whatever method you usually use.

• RStudio desktop. You can download this from the University’s Company Portal software repository. Alternatively, visit https://posit.co/download/rstudio-desktop/. We will use RStudio to work with R notebooks throughout the course. If you have another way of working with R notebooks that you prefer, then you are welcome to use this, but we recommend using RStudio if you’re unsure.

• Ensure you have following R packages installed:

  • tidyverse
  • palmerpenguins (This contains a dataset we’ll use in examples during the course.)
  • readxl

  If you need a refresher on installing R packages, consult the resources page. (Note: if you use a package management system for managing your R packages, such as renv, then you are of course free to use this.)

Finally, you will also need to download the course materials (select whichever archive format works best for you):

• Zip archive: course_materials.zip
• Tar gzip archive: course_materials.tar.gz

These contain R notebooks and datasets that will be worked through in the course sessions. The notebooks are designed to work with the relative directory structure in the archives, so it’s best not to change this structure! We suggest you place the archive in a directory specifically for this course and then unpack the contents within this directory. You will also find an R project file Working_with_data_in_R.Rproj: double-clicking on this should open RStudio at the correct directory containing all the notebooks.