Only open to master’s students in Psychology with specialisation Methodology and Statistics.
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, 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:
Acquires basic knowledge of how R works: understand objects like numbers, vectors, matrices, data frames and plots; install and load packages; understand work directory and workspace; operate help function;
Feels comfortable operating R in general: do calculations with objects; generate random data; understand element wise operations; make basic plots;
Feels comfortable using functions and packages: use functions; understand input and output of functions; understand documentation of packages and functions; and
Acquires basic programming skills: write functions; use if and else statements; use for- and while-loops; write programs with multiple functions.
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 7-9 computer lab sessions
Graded assignments (50%) and an exam (50%).
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 available from “The Comprehensive R Archive Network”
Paradis, E. 2005. R for Beginners. (http://cran.r-project.org/doc/contrib/Paradis-rdebuts_en.pdf)
Venables, W.N., Smith, D.M. and the R Core Team. 2013. An Introduction to R. (http://www.cran.r-project.org/doc/manuals/R-intro.pdf)
Owen, W.J. 2010. The R Guide (http://cran.r-project.org/doc/contrib/Owen-TheRGuide.pdf)
Material supplied during the course
Dr. Frank Busing