| Detailinformationen |
| Anmeldevoraussetzungen |
(*)keine
|
| Quellcurriculum |
Masterstudium Statistics and Data Science 2024W |
| Ziele |
(*)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.
|
| Lehrinhalte |
(*)Computer arithmetic, methods of non-linear optimization and root finding, EM algorithm, pseudorandom number generation, numerical integration,
Jackknife and bootstrap, permutation tests
|
| Beurteilungskriterien |
(*)Exam
Project
|
| Lehrmethoden |
(*)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
|
| Abhaltungssprache |
Englisch |
| Literatur |
(*)Slides
Supplementary reading will be announced each semester.
|
| Lehrinhalte wechselnd? |
Nein |
| Äquivalenzen |
(*)in collaboration with 951STMOSANK14: KV Survival Analysis (4 ECTS) equivalent to
4MSCVDPR: PR Computerintensive Verfahren in der Datenanalyse (6 ECTS)
|
