Upcoming courses

Research Techniques

Course: Introduction into R

With over two million users worldwide R is becoming the leading software package for statistics and data science. It is freely available and has many utilities and possibilities for e.g. basic and advanced statistical analysis; creating sophisticated graphs; data handling; and writing software. As such R is a very convenient software package since it allows you to create scripts for data handling, analysis, and visualization and to have your results and figures for your paper in one run, which cannot be done with statistical packages like SPSS, SAS, or Stata.

However for many researchers it is not directly clear how to use R, because of the R language and the way of reasoning. We would therefore like to introduce the students to and familiarize them with R. After finishing this introductory R course, you will master some very valuable R skills and will be ready to do your own data analyses.

In the first part of this course you will learn the basics of R through short lectures and many computer exercises. The following topics will be treated: the R language, R variables (objects), R data structures, reading and writing data files, manipulating datasets, performing basic statistics (only one day!), making graphs, simulations, and creating functions.

In the second part you will be given an assignment (case study) that challenges you to utilize of the lessons from the first part. You will work out the assignment with a fellow student under the supervision of the teachers. You will write a script that explains the steps followed, explains the problems that you encountered and how you solved them, and make a (digital) poster to present the results. The You will get feedback on this report.

This course is aimed at people who'd like to start using R. No previous experience in programming languages or data science is required, but knowledge of basic statistics (e.g. Student’s t-test, chi-square test, correlations, regression analysis) is required. As a preparation for the course you are requested to read a tutorial on the very basics of R and already perform some simple exercises.

The course days are on:

March 9     09:00-13:00 hours

March 10   09:00-13:00 hours

March 12   09:00-13:00 hours

March 13   09:00-13:00 hours

March 16   09:00-13:00 hours

March 17   09:00-13:00 hours

March 18   13:00-17:00 hours

March 20   09:00-13:00 hours

March 23   13:00-17:00 hours

March 25   09:00-13:00 hours    



Intended for: PhD students, Research Master Students, and other interested researchers


Examination: participation is required (report will be graded upon request, e.g. for CPE research master, Epidemiology registration)



March 9–25, 2020



EC (without exam)


Location address

to be announced

Course coordinator

  • I.M. (Ilja) Nolte, PhD




fully booked

Deadline for registration

February 20, 2020


Register for the waiting list

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