Open course material
Learn R
Free, hands-on course material on R, RStudio, the tidyverse and reproducible data science practice.
Built for our PhD course at SDU, open to everyone.
What you will learn
The material follows the data science workflow: import, tidy, visualise, model and communicate.
R and RStudio basics
Console, scripts, projects and Quarto documents — plus how to get good help from docs and AI.
Import and tidy data
Read data from files, then reshape, filter and summarise it with dplyr and tidyr. Handle factors and missing values along the way.
Visualise
Build clear, publication-ready graphics with ggplot2 and the grammar of graphics.
Statistics
Common hypothesis tests and regression models, reported clearly.
Tables and reports
Produce descriptive and model tables and render complete reports to HTML, Word or PDF.
Reproducible research
Organise projects so others (including future you) can rerun your analyses.
The 4-day PhD course
Built for our 4-day PhD course at SDU, mixing short lectures with hands-on exercises and ending in a home assignment on your own dataset. The same material is used in other courses and workshops and is freely available for self-paced learning.
Good to know
- No prior R experience required
- Bring your own laptop
Navigation. The sidebar on the left lists all pages by section. At the bottom of each page you will find links to the previous and next pages, and the search function is in the top-right corner.
Collapsible boxes. Some content is hidden in collapsible boxes like this one. Click the title bar to open or close a box.
Tabs. Some content is split across tabs, for example instructions for different operating systems:
Microsoft Windows relevant content
MacOS relevant content
Linux relevant content
Screenshots. Screenshots are shown in a thin blue frame. They are images, so you cannot copy their text, their links do not work, and Google Translate will not translate them.
