| Detailed information |
| Pre-requisites |
keine
|
| Original study plan |
Master's programme Statistics and Data Science 2024W |
| Objectives |
Students learn to understand the theory and the correct application of advanced topics in computational statistics as well as to independently
implement and apply selected methods.
|
| Subject |
Computer arithmetic, methods of non-linear optimization and root finding, EM algorithm, pseudorandom number generation, numerical integration,
Jackknife and bootstrap, permutation tests
|
| Criteria for evaluation |
Exam
Project
|
| Methods |
Lecture by instructor; Discussion of the projects, where the solution is presented by the students in a project report; Independent development and application of computational statistical methods
|
| Language |
English |
| Study material |
Slides
Supplementary reading will be announced each semester.
|
| Changing subject? |
No |
| Corresponding lecture |
in collaboration with 951STMOSANK14: KV Survival Analysis (4 ECTS) equivalent to
4MSCVDPR: PR Computerintensive Verfahren in der Datenanalyse (6 ECTS)
|
