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Statistical computing with R


Admission requirements

Students are assumed to be attending (or have previously attended) the courses "Statistics & Probability", "Mathematics for Statisticians" and "Generalized Linear Models and Linear Algebra" from the MSc in Statistics and Data Science.
To fully benefit from this course, you should be familiar with elementary concepts from linear algebra, calculus, probability theory and statistical inference.


Since its inception in 2000, R has grown to be one of the most versatile and widely used programming languages in statistics and data science. In this course you will be introduced to programming, data analysis and statistical computing with R.
Topics covered will include techniques to manage data, perform simple statistical analyses, produce data visualizations, programming and debugging code, and implementing simple statistical methods.

Course objectives

By the end of the course, students should be able to use R and RStudio to:

  • import and manipulate data;

  • perform statistical analyses of simple datasets;

  • produce data visualizations;

  • write simple R programs and functions;

  • write neat and annotated code;

  • generate reproducible reports (R Markdown).


See the Leiden University students' website for the Statistics and Data Science programme.

Mode of Instruction

The course will consist of a combination of lectures, computer practicals and self-study.

Assessment method

The final grade consists of a midterm exam (50%) and a final exam (50%). The midterm exam will cover the topics presented in the first half of the course, whereas the final exam topics from the whole course (but mostly from the second half). To pass the exam, the unrounded weighted average of the midterm and final exam should be at least 5.5.

The retake exam is a single exam covering the whole course. The final grade based on the retake exam is just the grade of the retake exam (100%). A grade of at least 5.5 is required to pass the retake exam.

Reading list

Braun, W. J., & Murdoch, D. J. (2021). A first course in statistical programming with R. Cambridge University Press.

Rizzo, M. L. (2019). Statistical computing with R. CRC Press.


Enroll in uSis to obtain the course material and course updates from Brightspace.

To be able to obtain a grade and the EC 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 participates in and registers for the first exam opportunity.