Course content

In statistics, we are used to search for the best predictors of some random variable. In many situations, however, we are interested in predicting a system's behavior under manipulations. For such an analysis, we require knowledge about the underlying causal structure of the system. In this course, we study concepts and theory behind causal inference.


MSc programme in Statistics
MSc Programme in Mathematics-Economics

Learning outcome


  • causal models versus observational models 
  • observational distribution, intervention distribution, and counterfactuals
  • graphical models and Markov conditions
  • identifiability conditions for learning causal relations from observational and/or interventional data


  • working with graphs and graphical models 
  • derivation of causal effects and predicting the result of interventional experiments
  • performing variable adjustment for computing causal effects
  • understanding of and ability to apply different methods for causal structure learning


  • causal reasoning
  • learning causal structure from data

4 hours lectures and 4 hours of exercises per week for 7 weeks.

See Absalon for a list of course literature.

Basic knowledge of probability theory (such as densities, conditional independence, and conditional distributions) and standard statistical tools (such as regression techniques and tests); e.g., it suffices to have passed StatMet and MStat (alternatively “MatStat” from previous years), Sand and Statistics A (or courses that are equivalent to these courses; Statistics A can be replaced by ModComp).
Basic knowledge of programming in R.

7,5 ECTS
Type of assessment
Oral examination
Type of assessment details
25 minutes oral exam without preparation time. No aids allowed.
Without aids
Marking scale
7-point grading scale
Censorship form
No external censorship
One internal examiner.
Criteria for exam assessment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 149
  • Exercises
  • 28
  • Exam
  • 1
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 4
No limit.
The number of seats may be reduced in the late registration period
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Leonard Henckel   (7-4e6b7469716b724673677a6e34717b346a71)

Leonard Henckel

Saved on the 18-07-2022

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