401-3632-00L Computational Statistics
| Semester | Spring Semester 2015 |
| Lecturers | M. Mächler, P. L. Bühlmann |
| Periodicity | yearly recurring course |
| Language of instruction | English |
Courses
| Number | Title | Hours | Lecturers | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 401-3632-00 V | Computational Statistics | 3 hrs |
| M. Mächler, P. L. Bühlmann | |||||||||
| 401-3632-00 U | Computational Statistics In the first week *only*, the exercises will be in a computer lab; on how to use R on these computers (will be used for exam, as well). | 2 hrs |
| M. Mächler, P. L. Bühlmann |
Catalogue data
| Abstract | "Computational Statistics" deals with modern methods of data analysis (aka "data science") for prediction and inference. An overview of existing methodology is provided and also by the exercises, the student is taught to choose among possible models and about their algorithms and to validate them using graphical methods and simulation based approaches. |
| Learning objective | Getting to know modern methods of data analysis for prediction and inference. Learn to choose among possible models and about their algorithms. Validate them using graphical methods and simulation based approaches. |
| Content | Course Synopsis: multiple regression, nonparametric methods for regression and classification (kernel estimates, smoothing splines, regression and classification trees, additive models, projection pursuit, neural nets, ridging and the lasso, boosting). Problems of interpretation, reliable prediction and the curse of dimensionality are dealt with using resampling, bootstrap and cross validation. Details are available via http://stat.ethz.ch/education/ . Exercises will be based on the open-source statistics software R (http://www.R-project.org/). Emphasis will be put on applied problems. Active participation in the exercises is strongly recommended. More details are available via the webpage http://stat.ethz.ch/education/ (-> "Computational Statistics"). |
| Lecture notes | lecture notes are available online; see http://stat.ethz.ch/education/ (-> "Computational Statistics"). |
| Literature | (see the link above, and the lecture notes) |
| Prerequisites / Notice | Basic "applied" mathematical calculus and linear algebra. At least one semester of (basic) probability and statistics. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 10 credits |
| Examiners | M. Mächler |
| Type | session examination |
| Language of examination | English |
| Repetition | The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit. |
| Mode of examination | written 180 minutes |
| Additional information on mode of examination | Prüfung enthält Aufgaben am Computer mit Benützung von R |
| Written aids | Ein A4-Blatt doppelseitig handgeschriebene Zusammenfassung. One sheet of paper (A4, front and back) with a hand-written summary. |
| This information can be updated until the beginning of the semester; information on the examination timetable is binding. | |
Learning materials
| Main link | Lecture notes "Computational Statistics" (C) Martin Maechler and Peter Buehlmann |
| Only public learning materials are listed. | |
Groups
| No information on groups available. |
Restrictions
| There are no additional restrictions for the registration. |
