Warning! The directory is not yet complete and will be amended until the beginning of the term.
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.