| Number | Title | ECTS | Hours | Lecturers |
|---|
| 401-3611-00L | Advanced Topics in Computational Statistics | 4 credits | 2V | M. H. Maathuis,
M. Mächler |
| Abstract | This lecture covers selected advanced topics in computational statistics, including various classification methods, the EM algorithm, clustering, handling missing data, and graphical modelling. |
| Learning objective | Students learn the theoretical foundations of the selected methods, as well as practical skills to apply these methods and to interpret their outcomes. |
| Content | The course is roughly divided in three parts: (1) Supervised learning via (variations of) nearest neighbor methods, (2) the EM algorithm and clustering, (3) handling missing data and graphical models. |
| Lecture notes | Lecture notes. |
| Prerequisites / Notice | We assume a solid background in mathematics, an introductory lecture in probability and statistics, and at least one more advanced course in statistics. |
| 401-5620-00L | Research Seminar on Statistics  | 0 credits | 2K | P. L. Bühlmann,
L. Held,
T. Hothorn,
M. H. Maathuis,
S. van de Geer,
M. Wolf |
| Abstract | Research colloquium |
| Learning objective | |
| 401-5640-00L | ZüKoSt: Seminar on Applied Statistics | 0 credits | 1K | M. Kalisch,
P. L. Bühlmann,
R. Furrer,
L. Held,
T. Hothorn,
M. H. Maathuis,
M. Mächler,
L. Meier,
M. Robinson,
C. Strobl,
S. van de Geer |
| Abstract | About 5 talks on applied statistics. |
| Learning objective | See how statistical methods are applied in practice. |
| Content | There will be about 5 talks on how statistical methods are applied in practice. |
| Prerequisites / Notice | This is no lecture. There is no exam and no credit points will be awarded. The current program can be found on the web:
http://stat.ethz.ch/events/zukost
Course language is English or German and may depend on the speaker. |
