Christina Heinze-Deml: Catalogue data in Spring Semester 2021

Name Dr. Christina Heinze-Deml
DepartmentMathematics
RelationshipLecturer

NumberTitleECTSHoursLecturers
401-4632-15LCausality Information 4 credits2GC. Heinze-Deml
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.
ObjectiveAfter this course, you should be able to
- understand the language and concepts of causal inference
- know the assumptions under which one can infer causal relations from observational and/or interventional data
- describe and apply different methods for causal structure learning
- given data and a causal structure, derive causal effects and predictions of interventional experiments
Prerequisites / NoticePrerequisites: basic knowledge of probability theory and regression