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Introduction to R and Statistical Computing


Important Note

  • All Semester II bachelor and master psychology courses and examinations (2020-2021) will be offered in an on-line format.

  • If it is safe and possible to do so, supplementary course meetings may be planned on-campus. However, attendance at these meetings will not be required to successfully complete Semester II courses.

  • All obligatory work groups and examinations will be offered on-line during Central European Time, which is local time in the Netherlands.

  • Information on the mode of instruction and the assessment method per course will be offered in Brightspace, considering the possibilities that are available at that moment. The information in Brightspace is leading during the Corona crisis, even if this does not match the information in the Prospectus.

Entry requirements

Only open to Master’s and Research Master’s students from Psychology.


R is a popular statistical programming environment, which provides a wide variety of statistical analysis tools, like data manipulation, model construction, simulations, and visualization. It can be used as data analysis software, but also as an effective programming language. In addition, R is available as Free Software, underlying code can be viewed and the researcher can make changes to suit his needs. Due to this open nature, R is highly flexible and can easily be extended, either by adding packages or programming new functions. Therefore R contains an ever-growing large collection of tools for data analysis, making it the primary tool of many researchers and a cutting edge environment for statisticians.

This course will give an introduction to R and computational statistics, handing a toolkit of theory and practice of the environment, making it both possible to use R in a variety of statistical analysis, and creating a base for acquiring further knowledge and skill.

Course objectives

Upon completion of this course, the student:

  • Knows how to use R and its environment and how to get help;

  • Knows how to handle simple data and functions;

  • Knows how to handle complex data and functions;

  • Knows how to handle graphs;

  • Knows how to handle different data analyses;

  • Knows how to program in R;

  • Knows how to do matrix algebra in R;

  • Knows how to find the optimum of a function; and

  • Knows how to perform Monte Carlo simulation and re-sampling.


For the timetables of your meetings, see the timetables page of your study programme. You will also find the enrolment codes here. Psychology timetables



Students need to enroll for meetings and examinations. Master’s course registration


Students are not automatically enrolled for an examination. They can register via uSis from 100 to 10 calendar days before the date. Students who are not registered will not be permitted to take the examination. Registering for exams

Mode of instruction

The course consists of self-study modules and about 8 online meetings in different compositions.

Assessment method

Asssessment for this course consists of 2 home assignments. The final grade is a weighted average of these 2 graded assignments.
The final assignment forms the basis of an online oral examination.

The Institute of Psychology follows the policy of the Faculty of Social and Behavioural Sciences to systematically check student papers for plagiarism with the help of software. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of this fraud policy.

Reading list

Manuals and articles are available from Brightspace during the course.

Contact information

Dr. Frank Busing (first semester)
Dr. Julian Karch (second semester