Universität Wien

040170 UK Statistics of high-dimensional and complex data (2021W)

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

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

The course will be held digitally. Each week, relevant materials will be posted in advance.

Also, live sessions will be scheduled (approximately once or twice per month) where the students can ask questions and where topics can be further discussed.

All relevant infos learning materials and links will be posted on Moodle on time!

  • Wednesday 06.10. 16:45 - 18:15 Digital
  • Wednesday 13.10. 16:45 - 18:15 Digital
  • Wednesday 20.10. 16:45 - 18:15 Digital
  • Wednesday 27.10. 16:45 - 18:15 Digital
  • Wednesday 03.11. 16:45 - 18:15 Digital
  • Wednesday 10.11. 16:45 - 18:15 Digital
  • Wednesday 17.11. 16:45 - 18:15 Digital
  • Wednesday 24.11. 16:45 - 18:15 Digital
  • Wednesday 01.12. 16:45 - 18:15 Digital
  • Wednesday 01.12. 18:30 - 20:00 Digital
  • Wednesday 15.12. 16:45 - 18:15 Digital
  • Wednesday 12.01. 16:45 - 18:15 Digital
  • Wednesday 19.01. 16:45 - 18:15 Digital
  • Wednesday 26.01. 16:45 - 18:15 Digital

Examination topics

Statistical theory presented in the lecture plus practical skills in R are necessary for this course.

Group 2

max. 35 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

The course will be held digitally. Each week, relevant materials will be posted in advance on MOODLE.

Also, live sessions will be scheduled (approximately once or twice per month) where the students can ask questions and where topics can be further discussed.

All relevant infos learning materials and links will be posted on Moodle on time!

  • Wednesday 06.10. 18:30 - 20:00 Digital
  • Wednesday 13.10. 18:30 - 20:00 Digital
  • Wednesday 20.10. 18:30 - 20:00 Digital
  • Wednesday 27.10. 18:30 - 20:00 Digital
  • Wednesday 03.11. 18:30 - 20:00 Digital
  • Wednesday 10.11. 18:30 - 20:00 Digital
  • Wednesday 17.11. 18:30 - 20:00 Digital
  • Wednesday 24.11. 18:30 - 20:00 Digital
  • Wednesday 01.12. 18:30 - 20:00 Digital
  • Wednesday 15.12. 18:30 - 20:00 Digital
  • Wednesday 12.01. 18:30 - 20:00 Digital
  • Wednesday 19.01. 18:30 - 20:00 Digital
  • Wednesday 26.01. 18:30 - 20:00 Digital

Examination topics

The course will be held mostly in German, but decent knowledge of English is necessary as some learning materials may be in English.

Information

Aims, contents and method of the course

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

Assessment and permitted materials

Midterm exam (on-site when possible)+ Project in R at the end of the semester

Minimum requirements and assessment criteria

The course will be held mostly in German, but decent knowledge of English is necessary as some learning materials may be in English.

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/

R Refresher:
R Graphics Cookbook: Practical Recipes for Visualizing Data - Winston Chang

All other relevant infos will be posted in Moodle.

Association in the course directory

Last modified: Fr 12.05.2023 00:12