Universität Wien
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040170 UK Statistics of high-dimensional and complex data (2020W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Summary

1 Milovic , Moodle
2 Milovic , Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Registration information is available for each group.

Groups

Group 1

Die Literatur zu dem Thema dieses Kurses ist durchweg auf Englisch. Daher sind auch die Kursmaterialien auf Englisch. Der Kurs kann auf Wunsch auf Deutsch gehalten werden, wobei es sinnvoller wäre den Kurs komplett auch auf Englisch zu halten.

max. 35 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

This course will be held online. All materials and information will be continuously updated in Moodle, which means that it is not necessary to be online on Mondays at 16:45.

  • Monday 05.10. 16:45 - 18:15 Digital
  • Monday 12.10. 16:45 - 18:15 Digital
  • Monday 19.10. 16:45 - 18:15 Digital
  • Monday 09.11. 16:45 - 18:15 Digital
  • Monday 16.11. 16:45 - 18:15 Digital
  • Monday 23.11. 16:45 - 18:15 Digital
  • Monday 07.12. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 14.12. 16:45 - 18:15 Digital
  • Monday 11.01. 16:45 - 18:15 Digital
  • Monday 18.01. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß

Group 2

max. 35 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

This course will be held online. All materials and information will be continuously updated in Moodle, which means that it is not necessary to be online on Mondays at 16:45.

  • Monday 05.10. 15:00 - 16:30 Digital
  • Monday 12.10. 15:00 - 16:30 Digital
  • Monday 19.10. 15:00 - 16:30 Digital
  • Monday 09.11. 15:00 - 16:30 Digital
  • Monday 16.11. 15:00 - 16:30 Digital
  • Monday 23.11. 15:00 - 16:30 Digital
  • Monday 30.11. 15:00 - 16:30 Digital
  • Monday 07.12. 15:00 - 16:30 Digital
  • Monday 14.12. 15:00 - 16:30 Digital
  • Monday 11.01. 15:00 - 16:30 Digital
  • Monday 18.01. 15:00 - 16:30 Digital
  • Monday 25.01. 15:00 - 16:30 Digital

Information

Aims, contents and method of the course

High-dimensional linear models, model selection, LASSO, Ridge, Multiple Testing, etc.

Assessment and permitted materials

2 exams + homework

Minimum requirements and assessment criteria

Examination topics

Reading list

Hastie, T.; Tibshirani, R. & Friedman, J. (2001), The Elements of Statistical Learning , Springer New York Inc. , New York, NY, USA .

https://web.stanford.edu/~hastie/ElemStatLearn/

Association in the course directory

Last modified: Fr 12.05.2023 00:12