040721 UK Selected Topics in Statistics (MA) (2023W)
Continuous assessment of course work
Labels
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 11.09.2023 09:00 to Fr 22.09.2023 12:00
- Deregistration possible until Fr 20.10.2023 23:59
Details
max. 30 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 03.10. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 10.10. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 17.10. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 24.10. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 31.10. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 07.11. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 14.11. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 21.11. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 28.11. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 05.12. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 12.12. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 09.01. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 16.01. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 23.01. 15:00 - 16:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
There is a written exam on theoretical topics 1 and 2 on 14.11.2023, as well as three exercise sheets with a programming part on topic 3 (provided on 28.11.2023, 12.12.2023, 16.01.2024). The exercise sheets should be submitted in a week and will be discussed in the exercise session.The use of AI tools (e.g. ChatGPT) for the production of texts is only permitted if they are expressly requested by the course leader (e.g. for individual work tasks).
Minimum requirements and assessment criteria
40 points for the written exam on topics 1 and 2
20 each exercise sheetThe grade results according to the scheme: 4 from 50 points, 3 from 63 points, 2 from 75 points, and 1 from 87 points.
20 each exercise sheetThe grade results according to the scheme: 4 from 50 points, 3 from 63 points, 2 from 75 points, and 1 from 87 points.
Examination topics
All topics covered in the lecture.
Reading list
Shao, J. (2003): Mathematical Statistics.
Robert, C. P. And Casella, G. (2004): Monte Carlo Statistical Methods.
Hoff, P. D. (2010): A First Course in Bayesian Statistical Methods.
Robert, C. P. And Casella, G. (2004): Monte Carlo Statistical Methods.
Hoff, P. D. (2010): A First Course in Bayesian Statistical Methods.
Association in the course directory
Last modified: We 18.10.2023 12:07
Get acquainted with concepts of Bayesian statistics: theoretical foundations, methodology and applications.
Learn how to implement computer-based procedures.Contents:
1. Decision Theory (admissibility and optimality, Bayes and minimax decisions)
2. Bayesian Estimation (Bayes formula, Bayes estimators, hierarchical and empirical Bayes methods)
3. Markov Chain Monte Carlo Methods (Slice Sampler, Gibbs Sampler, Metropolis-Hastings, monitoring convergence, credible intervals)Methods:
Lecture with exercise sessions.
Lecture notes, exercise sheets and data will be available online.
Students are supposed to code in statistical software.