The course will cover topics in computational statistics including:

(o) numerical linear algebra relevant for statistical methodology,

(o) optimization methods relevant for statistical methodology,

(o) stochastic simulation techniques,

(o) bootstrapping and simulation-based inference methods.

Students know about advantages and pitfalls of methods in computational statistics as well as are able to independently implement and apply selected methods.

For this course participation is obligatory. Students are allowed to miss a maximum of 20% (no matter if excused or not excused).

This course is taught as lectures and tutorials combined with assignments and a project. In combination with the lectures, the assignments and the project help students to consolidate and expand their understanding of the methods discussed in the lectures.

Grading is based on assignments (30%), a project (30%) and a presentation (40%).

bettina.gruen@wu.ac.at