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Statistical computing with R


Admission requirements

Knowledge of elementary calculus and statistics, e.g. integration, derivation, t-tests, chi-square tests, analysis of variance, linear and logistic regression. Mastery of the basics in TeX, coding in html, and R Markdown in your own time.

Make sure you have a laptop available during each lecture with the latest version of R and RStudio (for details see Blackboard)


to be announced.

Course objectives

Compose code in R (mainly the S3 object-oriented system) to solve computation problems relevant for statistical science by

  • using consistent style in programming – using version control – applying appropriate programming structures – designing functions

  • developing visualisation functions for data and (intermediate) results

  • performing simulation / (re)sampling studies

Mode of Instruction

This course is a combination of lectures and lab sessions.

Time Table

For the course days, course location and class hours check the Time Table under the
tab “Statsci Students —> Program Schedule” at

Assessment method

Home assignments (1/3) and an examination (2/3) at the end of the course.

Compulsory home assignments will be distributed at the end of each lecture and have to be uploaded on blackboard before the following lecture.

The written exam consists of programming exercises for which a laptop should be

Date information about the exam and resit can be found in the time table (see the time table header). The room and building for the exam will be announced on the electronic billboard, to be found at the opposite of the entrance, the content can also be viewed here.

Reading list

The art of R programming. Norman Matloff, No Starch Press 2011, ISBN: 978-1-59327-384-2

Course Registration

Enroll in Blackboard for the course materials and course updates.

To be able to obtain a grade and the ECTS for the course, sign up for the (re-)exam in uSis ten calendar days before the actual (re-)exam will take place. Note, the student is expected to participate actively in all activities of the program and therefore uses and registers for the first exam opportunity.

Exchange and Study Abroad students, please see the Prospective students website for information on how to apply.

Contact information

mkampert [at] math [dot] leidenuniv [dot] nl


  • This is a compulsory course in the Master’s programme Statistical Science for the Life & Behavioural sciences.