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Computational Statistics


Admission requirements

The topics covered in this course require good knowledge and understanding of calculus, probability theory, inferential statistics (point estimation, likelihood theory, confidence intervals, hypothesis testing), and programming with R. The courses “Mathematics for Statisticians”, “Statistics and Probability” and “Statistical Computing with R” from the MSc in Statistics and Data Science are prerequisites for this course. Students are also expected to have a basic understanding of the linear and logistic regression models.


This course will introduce you to the field of computational statistics, which can be loosely defined as a set of numerical methods and algorithms that can be employed to solve a well-defined statistical problem. We will discuss the mathematical and statistical foundations that such methods rely on, and show how you can implement them in R. In particular, we will focus on the following topics:
1. Methods for the generation of random variables
2. The Monte Carlo method
3. Applications of the Monte Carlo method
4. Variance reduction methods
5. Numerical integration and root finding algorithms
6. The bootstrap
7. Applications of the bootstrap
8. Permutation tests

Course Objectives

By the end of the course, students are expected to:
1. understand the mathematical and statistical foundations of the methods covered in the course (see “Description”);
2. be able to recognize when a method can be applied to solve a given problem;
3. know how to solve relevant statistical problems using such methods;
4. be able to implement the methods and algorithms using R;
5. be able to interpret critically the results yielded by the application of such methods.


You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.
MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).
For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.

Mode of Instruction

A combination of lectures and computer practicals. To fully benefit from the practicals, it is recommended that you bring your own laptop with R and RStudio installed.

Assessment method

A written exam at the end of the course. The grade of the written exam should be at least 5.5 to get a pass.

Reading list

Rizzo, M. L. (2019). Statistical Computing with R. CRC Press.
When relevant, additional references will be provided at the end of each lecture.


It is the responsibility of every student to register for courses with the new enrollment tool MyStudyMap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.

Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.
Extensive FAQ's on MyStudymap can be found here.


compstatleiden [at] gmail [dot] com