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Computational Statistics with R


Entry requirements

Only open to Master student with specialisation Methodology and Statistics in Psychology.

This course is offered twice a year


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 a short introduction to R and extended 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.

Brightspace contains the most recent information on all aspects of the course.

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 most data and important functions;

  • Knows how to handle different graphics;

  • Knows how to perform different data analyses;

  • Knows how to use R Markdown for presentations;

  • Knows how to program in R;

  • Knows how to do matrix algebra in R;

  • Knows how to find the (local and global) optimum of functions;

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


For the timetable of this course please refer to MyTimetable



Students must register themselves for all course components (lectures, tutorials and practicals) they wish to follow. You can register up to 5 days prior to the start of the course.


You must register for each exam in My Studymap at least 10 days before the exam date. You cannot take an exam without a valid registration in My Studymap. Carefully read all information about the procedures and deadlines for registering for courses and exams.

Exchange students and external guest students will be informed by the education administration about the current registration procedure.

Mode of instruction

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

Assessment method

Assessment for this course consists of about 8 master assignments, one assignment every week, and one final assignment. The final grade is an unbalanced weighted average of these graded assignments. The final assignment forms the basis for an oral examination. Resits are discussed directly after the oral examination and have a lower maximum grade.

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. All students are required to take and pass the Scientific Integrity Test with a score of 100% in order to learn about the practice of integrity in scientific writing. Students are given access to the quiz via a module on Brightspace. 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, tutorials, cheat sheet, and articles are available from Brightspace during the course.

Contact information

Dr. Frank Busing