NMAK17001U Causality

Volume 2021/2022
Education

MSc programme in Statistics

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.

Learning Outcome

Knowledge:

  • 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


Skills:

  • 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


Competences:

  • causal reasoning
  • learning causal structure from data

See Absalon for a list of course literature.

Basic knowledge of probability theory and regression, e.g. Sand (alternatively MI from previous years), Stat1 or equivalent courses.
Basic knowledge of programming in R.

Academic qualifications equivalent to a BSc degree is recommended.
4 hours lectures and 4 hours of exercises per week for 7 weeks.
  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 149
  • Exercises
  • 28
  • Exam
  • 1
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Oral examination
25 minutes oral exam without preparation time. No aids allowed.
Exam registration requirements

There will be between 4 and 6 group assignments (up to two students), which the students have to hand in. All assignments except for one need to get approved.

Aid
Without aids
Marking scale
7-point grading scale
Censorship form
No external censorship
One internal examiner.
Re-exam

25 minutes oral exam without preparation time. No aids allowed. If not enough assignments have been approved during the course, sufficiently many non-approved assignment(s) must be handed in no later than three weeks before the beginning of the re-exam week. The assignments must be approved before the re-exam.

Criteria for exam assesment

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