401-4620-00L Statistics Lab
|Dozierende||M. Kalisch, M. H. Maathuis, L. Meier, N. Meinshausen|
|Periodizität||jährlich wiederkehrende Veranstaltung|
|Kommentar||Maximale Teilnehmerzahl: 27|
|Kurzbeschreibung||"Statistics Lab" is an Applied Statistics Workshop in Data Analysis. It|
provides a learning environment in a realistic setting.
Students lead a regular consulting session at the Seminar für Statistik
(SfS). After the session, the statistical data analysis is carried out and
a written report and results are presented to the client. The project is
also presented in the course's seminar.
|Lernziel||- gain initial experience in the consultancy process |
- carry out a consultancy session and produce a report
- apply theoretical knowledge to an applied problem
After the course, students will have practical knowledge about statistical
consulting. They will have determined the scientific problem and its
context, enquired the design of the experiment or data collection, and
selected the appropriate methods to tackle the problem. They will have
deepened their statistical knowledge, and applied their theoretical
knowledge to the problem. They will have gathered experience in explaining
the relevant mathematical and software issues to a client. They will have
performed a statistical analysis using R (or SPSS). They improve their
skills in writing a report and presenting statistical issues in a talk.
|Inhalt||Students participate in consulting meetings at the SfS. Several consulting|
dates are available for student participation. These are arranged
-During the first meeting the student mainly observes and participates in
the discussion. During the second meeting (with a different client), the
student leads the meeting. The member of the consulting team is overseeing
(and contributing to) the meeting.
-After the meeting, the student performs the recommended analysis, produces
a report and presents the results to the client.
-Finally, the student presents the case in the weekly course seminar in a
talk. All students are required to attend the seminar regularly.
|Literatur||The required literature will depend on the specific statistical problem|
under investigation. Some introductory material can be found below.
|Voraussetzungen / Besonderes||Prerequisites: |
Sound knowledge in basic statistical methods, especially regression and, if
possible, analysis of variance. Basic experience in Data Analysis with R
Useful background lectures and material:
-Applied Statistical Regression (Dr. Marcel Dettling)
-Angewandte statistische Regression, mit Ergänzung
(Prof. Werner Stahel, Dr. Markus Kalisch)
-Applied Analysis of Variance and Experimental Design (Prof. M Müller) http://stat.ethz.ch/education/semesters/as2010/anova
-W. Stahel, Statistische Datenanalyse: Eine Einführung für
Naturwissenschaftler, (5. Auflage), Vieweg, 2005.
Useful material on Statistical Software (R and/or SPSS):
-401-6215-00L Using R for Statistical Data Analysis and Graphics (Dr. M. Mächler, Dr. A. J. Papritz, Dr. C. B. Schwierz). An older version of this course can be found on: http://stat.ethz.ch/ stahel/courses/R/
-An Introduction to R. http://stat.ethz.ch/CRAN/doc/manuals/R-intro.pdf
-SPSS Course and Exercises: ftp://stat.ethz.ch/U/sfs/SPSSKurs/
-Andy Field, Discovering Statistics Using SPSS, 3rd Edition, 2009, SAGE.