447-6273-00L Bayes Methods
| Semester | Autumn Semester 2020 |
| Lecturers | Y.‑L. Grize |
| Periodicity | two-yearly recurring course |
| Language of instruction | German |
| Comment | Special Students "University of Zurich (UZH)" in the Master Program in Biostatistics at UZH cannot register for this course unit electronically. Forward the lecturer's written permission to attend to the Registrar's Office. Alternatively, the lecturer may also send an email directly to registrar@ethz.ch. The Registrar's Office will then register you for the course. |
Courses
| Number | Title | Hours | Lecturers | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 447-6273-00 G | Bayes-Methoden
 Blockkurs. Weitere Informationen unter http://stat.ethz.ch/wbl/wbl 09.11.20 16.11.20 23.11.20 30.11.20 07.12.20 14.12.20 Leistungskontrolle am 11.01.2021 | 21s hrs |
| Y.‑L. Grize |
Catalogue data
| Abstract | conditional probability; bayes inference (conjugate distributions, HPD-areas; linear and empirical bayes); determination of the a-posteriori distribution through simulation (MCMC with R2Winbugs); introduction to multilevel/hierarchical models. |
| Objective | |
| Content | Bayes statistics is attractive, because it allows to make decisions under uncertainty where a classical frequentist statistical approach fails. The course provides an introduction into bayesian methods. It is moderately mathematically technical, but demands a flexibility of mind, which should not underestimated. |
| Literature | Gelman A., Carlin J.B., Stern H.S. and D.B. Rubin, Bayesian Data Analysis, Chapman and Hall, 2nd Edition, 2004. Kruschke, J.K., Doing Bayesian Data Analysis, Elsevier2011. |
| Prerequisites / Notice | Prerequisite:Basic knowledge of statistics; Knowledge of R. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 2 credits |
| Examiners | Y.-L. Grize |
| Type | ungraded semester performance |
| Language of examination | German |
| Repetition | Repetition possible without re-enrolling for the course unit. |
Learning materials
| No public learning materials available. | |
| Only public learning materials are listed. |
Groups
| No information on groups available. |
Restrictions
| General |  : Special students and auditors need a special permission from the lecturers |
Offered in
| Programme | Section | Type | |
|---|---|---|---|
| CAS in Applied Statistics | Further Courses | W |  |
| DAS in Applied Statistics | Electives | W | |
| Statistics Master | Statistical and Mathematical Courses | W | |
| Statistics Master | Subject Specific Electives | W | |