040690 UK Generalized Linear Model (UK) (2022S)
Continuous assessment of course work
Labels
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 07.02.2022 09:00 to Mo 21.02.2022 12:00
- Registration is open from Th 24.02.2022 09:00 to Fr 25.02.2022 12:00
- Deregistration possible until Mo 14.03.2022 23:59
Registration information is available for each group.
Groups
Group 1
max. 35 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Abschlusstest am 30.06.22 für beide Gruppen gemeinsam
Thursday
03.03.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
10.03.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
17.03.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
24.03.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
31.03.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
07.04.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
28.04.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
05.05.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
12.05.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
19.05.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
02.06.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
09.06.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
23.06.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
30.06.
16:45 - 18:15
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Group 2
max. 35 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Abschlusstest am 30.06.22 für beide Gruppen gemeinsam
Thursday
03.03.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
10.03.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
17.03.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
24.03.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
31.03.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
07.04.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
28.04.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
05.05.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
12.05.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
19.05.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
02.06.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
09.06.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
23.06.
15:00 - 16:30
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
30.06.
16:45 - 18:15
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
There are two term papers, one on Topic 1 and one on Topics 2 and 3.
The first term paper will be made public on April 7th and is due by 11:59pm on April 24th.
The second term paper will be assigned on June 2nd and is due by June 22nd, 11:59pm.
Each will address theoretical and practical problems, the latter to be solved using R.
In addition, a written final exam will be given on June 30th in presence on the theoretical contents of the whole course.
The first term paper will be made public on April 7th and is due by 11:59pm on April 24th.
The second term paper will be assigned on June 2nd and is due by June 22nd, 11:59pm.
Each will address theoretical and practical problems, the latter to be solved using R.
In addition, a written final exam will be given on June 30th in presence on the theoretical contents of the whole course.
Minimum requirements and assessment criteria
Up to 30 points are awarded for each term paper and up to 40 points for the final exam.
The grade is calculated according to the following scheme: 4 at 50 points, 3 at 63 points, 2 at 75 points, 1 at 87 points.
The grade is calculated according to the following scheme: 4 at 50 points, 3 at 63 points, 2 at 75 points, 1 at 87 points.
Examination topics
Topics covered in the lecture.
Reading list
Fahrmeir, Kneib, Lang (2007): Regression: Modelle, Methoden und Anwendungen
Dobson (2001): An introduction to generalised linear models
Nelder, McCullagh (1989): Generalised linear models
Galecki, Burzykowski (2013): Linear Mixed-Effects Models Using R
Dobson (2001): An introduction to generalised linear models
Nelder, McCullagh (1989): Generalised linear models
Galecki, Burzykowski (2013): Linear Mixed-Effects Models Using R
Association in the course directory
Last modified: Th 03.03.2022 16:08
Exercises on real data sets using R will provide a basic understanding of the theoretical and practical challenges of statistical modeling.