Lukas Meier: Catalogue data in Spring Semester 2020 |
Name | Dr. Lukas Meier |
Address | Seminar für Statistik (SfS) ETH Zürich, HG G 15.2 Rämistrasse 101 8092 Zürich SWITZERLAND |
Telephone | +41 44 632 97 49 |
lukas.meier@stat.math.ethz.ch | |
URL | http://stat.ethz.ch/~meier/ |
Department | Mathematics |
Relationship | Lecturer |
Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|
401-0620-00L | Statistical Consulting | 0 credits | 0.1K | M. Kalisch, L. Meier | |
Abstract | The Statistical Consulting service is open for all members of ETH, including students, and partly also to other persons. | ||||
Objective | Advice for analyzing data by statistical methods. | ||||
Content | Students and researchers can get advice for analyzing scientific data, often for a thesis. We highly recommend to contact the consulting service when planning a project, not only towards the end of analyzing the resulting data! | ||||
Prerequisites / Notice | This is not a course, but a consulting service. There are no exams nor credits. Contact: beratung@stat.math.ethz.ch Tel. 044 632 2223 or 044 632 34 30 Requirements: Knowledge of the basic concepts of statistics is desirable. | ||||
401-4620-00L | Statistics Lab ![]() Number of participants limited to 27. | 6 credits | 2S | M. Kalisch, M. H. Maathuis, M. Mächler, L. Meier, N. Meinshausen | |
Abstract | "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. | ||||
Objective | - 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. | ||||
Content | Students participate in consulting meetings at the SfS. Several consulting dates are available for student participation. These are arranged individually. -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. | ||||
Lecture notes | n/a | ||||
Literature | The required literature will depend on the specific statistical problem under investigation. Some introductory material can be found below. | ||||
Prerequisites / Notice | Prerequisites: Sound knowledge in basic statistical methods, especially regression and, if possible, analysis of variance. Basic experience in Data Analysis with R. | ||||
401-5640-00L | ZüKoSt: Seminar on Applied Statistics ![]() | 0 credits | 1K | M. Kalisch, A. Bandeira, P. L. Bühlmann, R. Furrer, L. Held, T. Hothorn, M. H. Maathuis, M. Mächler, L. Meier, N. Meinshausen, M. Robinson, C. Strobl, C. Uhler, S. van de Geer | |
Abstract | 5 to 6 talks on applied statistics. | ||||
Objective | Kennenlernen von statistischen Methoden in ihrer Anwendung in verschiedenen Gebieten, besonders in Naturwissenschaft, Technik und Medizin. | ||||
Content | In 5-6 Einzelvorträgen pro Semester werden Methoden der Statistik einzeln oder überblicksartig vorgestellt, oder es werden Probleme und Problemtypen aus einzelnen Anwendungsgebieten besprochen. 3 bis 4 der Vorträge stehen in der Regel unter einem Semesterthema. | ||||
Lecture notes | Bei manchen Vorträgen werden Unterlagen verteilt. Eine Zusammenfassung ist kurz vor den Vorträgen im Internet unter http://stat.ethz.ch/talks/zukost abrufbar. Ankündigunen der Vorträge werden auf Wunsch zugesandt. | ||||
Prerequisites / Notice | Dies ist keine Vorlesung. Es wird keine Prüfung durchgeführt, und es werden keine Kreditpunkte vergeben. Nach besonderem Programm. Koordinator M. Kalisch, Tel. 044 632 3435 Lehrsprache ist Englisch oder Deutsch je nach ReferentIn. Course language is English or German and may depend on the speaker. | ||||
447-0990-00L | Workshop ![]() Only for DAS in Applied Statistics. | 1 credit | 1S | L. Meier | |
Abstract | In the workshop each participant gives a short talk about a recent statistical problem encountered in their daily work. | ||||
Objective | Presentation of a statistical problem, getting to know different applications of statistical methodology. | ||||
701-0105-00L | Mathematics VI: Applied Statistics for Environmental Sciences Requirement: enrollment of 401-0624-00L Mathematics IV: Statistics or similar lecture. | 3 credits | 2G | C. Bigler, M. Kalisch, L. Meier | |
Abstract | Statistical methods from current publications in environmental sciences are presented and applied. Students are enabled to understand the methods, clean datasets, analyse them using the software package R and present the results in a suitable form. They will be able to describe strengths and weaknesses of the methods for given fields of application. | ||||
Objective | Students are able to - use suitable statistical methods for data analysis in their subject area. - characterize data sets using explorative methods - check the suitability of data sets to answer a given question, prepare data sets for import to a statistics program and conduct the analysis. - interpret statistical analyses and process them graphically for use in presentations and publications. - describe the basics of statistical methods used in current publications. - use the software package R for statistical analysis | ||||
Content | Statistische Methoden: Regression (lineare Modelle; generalisierte lineare Modelle, GLMs); Varianzanalyse (ANOVA); gemischte Modelle für gruppierte Daten (mixed-effects models); Fragebogenstatistik; Tests (t Test) Werkzeuge: Explorative Datenanalyse für Hypothesenbildung; Auswahlverfahren für geeignete statistische Verfahren; Datenaufbereitung (Excel -> R; Datenbereinigung); graphische Darstellung von Resultaten; statistische Verfahren in Publikationen erkennen. Wir arbeiten mit dem Softwarepaket R. Form: Im Wochenrhythmus finden alternierend Einführungen in eine neue Methode und Übungsstunden zum Thema statt. | ||||
Prerequisites / Notice | Besuch von "Mathematik IV: Statistik" oder vergleichbare Lehrveranstaltung. Die Schlussprüfung findet am Freitag 12.6.2020 (9:00 - 10:30) statt. |