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.
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 handle optimization, that is, finding the optimum of a function; and
- knows how to perform random number generation, Monte Carlo simulation, and re-sampling.
For the timetables of your lectures, work groups and exams, please select your study programme in:
Students need to enroll for lectures and work group sessions.
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 5 2-hour lectures and 8 2-hour work group sessions.
The final grade is based on 8 graded assignments.
The Faculty of Social and Behavioural Sciences has instituted that instructors use a software programme for the systematic detection of plagiarism in students’ written work. In case of fraud disciplinary actions will be taken. Please see the information concerning fraud.
Manuals and articles are available from Blackboard during the course.
Dr. Frank Busing