Introduction to R

This course is fully booked. Registration has been closed.
Another round will probably start early in the Fall, 2024.nPeople who were on the waiting list (till 22 February 2024) will be given priority.

R ( is a programming language and software environment for carrying out computations, manipulating and analyzing data, and creating various types of plots and graphics. R has become the 'lingua franca of statistics' and the software of choice for analyzing data in various disciplines.

Moreover, R is free, open-source, and runs on various platforms (Windows, MacOS, Linux, etc.). However, for many researchers, getting up and running with R remains a hurdle due to the command-driven nature of the software. The purpose of this course is to lay the necessary foundation for becoming a proficient R user.

Emphasis here is more on the general syntax as used in R and less on the statistical details of the various procedures.



Dr. Wolfgang Viechtbauer
Department of Psychiatry and Neuropsychology
Phone: +31 (43) 388-4170


Familiarity with basic statistical concepts and methods as used in the health, social, and natural sciences is helpful when following the course.

Course participants need to have the current version of R installed (which can be downloaded from https://cran.r- Also, while not necessary, installing RStudio (an integrated development environment for R) is highly recommended (which can be downloaded from


  • history of R
  • basic data structures
  • data import/export
  • data inspection
  • data manipulation
  • graphing data
  • t-tests and analysis of (co)variance (*)
  • linear regression (*)
  • analyzing categorical data / logistic regression (*)
  • survival analysis and Cox models (*)
  • mixed-effects models (*)
  • add-on packages
  • basic programming structures
  • writing functions
  • writing documents with Rmarkdown

(*) Emphasis here is more on the general syntax as used in R and less on the statistical details of the various procedures.


Four full days (starting at 9:00 and ending around 17:00, with a lunch break around 12:00 and coffee/tea breaks as needed)


Interactive hands-on lectures.


There are no required readings but the following book is a popular reference:
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage

Course fees

PhD candidates (Promovendi) of FHML, MaCSBIO, M4I and MERLN: no fee
Master students: no fee (*)
Other: €500,00
(*) PhD candidates and other participants are given preference. If some spots are still available, then Master students can apply.

Course dates

Dates Time Location
29-01-2024 9.00-17.00 hrs.  Online
31-01-2024 9.00-17.00 hrs.  Online
05-02-2024 9.00-17.00 hrs.  Online
07-02-2024 9.00-17.00 hrs.  Online


PhD secretary
Available Monday until Thursday: 9 am – 5 pm
Friday morning: 9 am – 1 pm

 +31 43 387 28 44
 Visitors address: Fac.Bur. FHML, P.Debeyelaan 15/ Dr. Van Kleeftoren, 2N2.004