Introduction to R – University of Copenhagen

Workshops and small courses

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?

  • Wednesday Aug 22, 9-16 and Thursday Aug 23, 9-12
  • Room A2-70.04 at Frederiksberg Campus (Thorvaldsensvej 40)
  • The second day is optional, and no new material will be presented

Who can participate?

  • The course is intended for people with no or little prior knowledge of R
  • The course is open for PhD students and employees at SCIENCE
  • The course is NOT open for students at Bachelor or Master level, and NOT open for people not associated to the Faculty of Science at UCPH
  • The number of participants is limited

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
  • The first day will consist of presentations as well as exercises. The second day is a follow-up day where you can continue working under guidance, but there will be no presentations

Which topics?

  • Introduction to R and R-studio
  • 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?

R and RStudio is avaliable for Windows, Mac and Linux

How to register?

  • Fill out the registration form
  • Notice that the workshop does not give any ECTS points

Questions?

  • If you have questions, then you are most welcome to contact Helle Sørensen from the Data Science Lab (helle@math.ku.dk).

Course material

  • Material for the course consists of slides for presentations, R code, and exercises, and it will appear here before the course.
  • Meanwhile, you may have a look at the material from 2017 

Literature

  • 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 confuses about the S)