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Statistical computing with R

Course 2015-2016

Admission requirements

Knowledge of elementary calculus and statistics, e.g. integration, derivation, t-tests, chi-square tests, analysis of variance, linear and logistic regression.

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


Nowadays computers have become an indispensable tool for statisticians in both industry and academia. The aim of this course is to familiarize students with the use of computers for statistical computation using the R environment. Topics that will be covered include among others: the basic structure of the R language, using and writing functions, producing graphics with R, efficient programming with R, and fitting statistical models.

Course objectives

At the end of the course we would like you to be able to…

  • solve computation problems within the S3 object-oriented system
  • extract information from objects obtained by applying existing R functions
  • extend existing R functions
  • construct new R functions
  • perform simple simulation studies in R
  • write reproducible reports in which R code is embedded
  • use a consistent style in programming

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 2015-16 under the
tab “Masters Programme” 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 to be uploaded on blackboard in the following week.

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

Exam and resit information about the date can be found in the Time Table 2015-16 pdf document under the tab “Masters Programme” at The exams take place in the Snellius building, the room will be announced on the electronic billboard, to be found at the opposite of the entrance, the content can also be viewed online at:
If the exam does not take place in the Snellius building, then an announcement will be sent via blackboard

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 of the specialisation Statistical Science for the Life & Behavioural sciences.