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 (40%), a project (30%) and a presentation (30%).

The final grade will be determined as follows: 1 (at least 91%), 2 (at least 81%), 3 (at least 66%), 4 (at least 51%), 5 (less than 51%).

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.

bettina.gruen@wu.ac.at