Introduction to R

The workshop will provide an introduction to the statistical software R, which is a flexible and extremely useful statistical toolbox. We will use the user interface Rstudio which provides a nice environment for working with R, and also work with Markdown documents. The course is aimed at researchers at SCIENCE (incl. PhD students), who need tools for data exploration, data analysis, and data visualization. The course will be practical and provide a mixture of presentations and hands-on exercises, both with focus on data examples and applications.

When and where?

  • The course last took place in August 2023. It is not clear yet when the next course will take place

Who can participate?

  • The course is intended for people with no or little prior knowledge of R
  • The course is free for PhD students and employees at SCIENCE (Faculty of Science, UCPH). The number of participants is limited.
  • There is a limited number of free seats for MSc students enrolled at a study at SCIENCE
  • There are 10 free seats for PhD students and employees at SUND (first come, first serve; additional participants pay the fee, see below; contact us if you want to know if all these seats are taken)
  • The cost is DKK 1500 for PhD students and employees associated to other faculties or universities
  • The course is NOT open for students at Bachelor level

What is going to happen?

  • Lecture-type introductions and overviews of basic functionalities
  • Hands-on exercises 
  • You are also welcome to bring your own data (as xlsx or csv files, say) and work with those if you prefer

Which topics?

  • Introduction to R and RStudio
  • Import of data into R, data manipulation
  • Graphics in R
  • Basic statistical analyses in R
  • Markdown
  • Possibly work with own data

What to do before the course?

  • Install R from
  • Install RStudio from
  • Install certain packages (via the Package Menu in RStudio): the tidyverse package, the readxl package, and the rmarkdown package. More info follows by email before the course.

How to register?

  • TBA


  • If you have questions, then you are most welcome to contact Helle Sørensen from the Data Science Lab (

Course material

  • zip-file with presentations, data, exercises, and solutions from 2023:
  • We recommend that you download the files before the course and save them in a separate folder on your laptop.


  • Wickham and Grolemund: R for Data Science. Available online here. Excellent introduction to data work, graphics, R programming.
  • Wickham: ggplot2. About graphics
  • Venables and Ripley: Modern Applied Statistics with S. About statistical analyses with R (don't get confused about the S)

Related course

  • Centre for Health Data Science (HeaDS) has a similar course, From Excel to R. There is room a small number of participants from SCIENCE (contact the organisers from HeaDS)