040170 UK Statistics of high-dimensional and complex data (2021W)
Continuous assessment of course work
Labels
REMOTE
Summary
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 is open from Mo 13.09.2021 09:00 to Th 23.09.2021 12:00
- Deregistration possible until Fr 15.10.2021 23:59
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 ChangAll other relevant infos will be posted in Moodle.
https://web.stanford.edu/~hastie/ElemStatLearn/R Refresher:
R Graphics Cookbook: Practical Recipes for Visualizing Data - Winston ChangAll other relevant infos will be posted in Moodle.
Association in the course directory
Last modified: Fr 12.05.2023 00:12