Student Seminar in Statistics:
Causality
Spring semester 2023
General information
| Lecturers | Peter Bühlmann, Nicolai Meinshausen, |
|---|---|
| Assistants | Juan Gamella, Malte Londschien, Cyrill Scheidegger |
| Lectures | Mon 16.00-18.00. Until further notice the lectures will take place in person: HG E 33.1 (class 1) and ML F 40 (class 2). | Moodle | >> |
| Course catalogue data | >> |
Course content
AbstractIn 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.
LiteratureWe will mainly follow the Causality course from 2021 by Dr. Christina Heinze-Deml, plus some additional papers covering further topics. Please refer to the Moodle course for more details.
NoticeEvery lecture will consist of an oral presentation highlighting key ideas of a selected topic by a group of students. Another group of students will be responsible for asking questions during the presentation and providing a discussion of the pros+cons of the papers at the end. Finally, an additional group is responsible for giving an evaluation on the quality of the presentations/discussions and provide constructive feedback for improvement.