Master’s students Psychology 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.
- Acquire 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.
- Feel comfortable operating R in general: do calculations with objects; generate random data; understand element wise operations; make basic plots.
- Feel comfortable using functions and packages: use functions; understand input and output of functions; understand documentation of packages and functions.
- Acquire basic programming skills: write functions; use if and else statements; use for- and while-loops; write programs with multiple functions.
Introduction to R and Statistical Computing (2014-2015):
Students need to enroll for lectures and work group sessions. Please consult the Instructions registration
Mode of instruction
The course consists of 9 computer lab sessions
Weekly graded assignments.
The Faculty of Social 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
Information on blackboard.leidenuniv.nl
- 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 WN, Smith DM , and the R Core Team (2013) An Introduction to R (http://www.cran.r-project.org/doc/manuals/R-intro.pdf)
- Owen WJ (2010) The R Guide (http://cran.r-project.org/doc/contrib/Owen-TheRGuide.pdf)
- Material supplied during the course
Dr. Matthijs J. Warrens
Tel.: +31 (0)71 527 3649