From 2 November 2020, the autumn semester 2020 will take place online. Exceptions: Courses that can only be carried out with on-site presence.
Please note the information provided by the lecturers via e-mail.

Lukas Meier: Catalogue data in Autumn Semester 2019

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
E-maillukas.meier@stat.math.ethz.ch
URLhttp://stat.ethz.ch/~meier/
DepartmentMathematics
RelationshipLecturer

NumberTitleECTSHoursLecturers
401-0620-00LStatistical Consulting0 credits0.1KM. Kalisch, L. Meier
AbstractThe Statistical Consulting service is open for all members of ETH, including students, and partly also to other persons.
ObjectiveAdvice for analyzing data by statistical methods.
ContentStudents 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 / NoticeThis is not a course, but a consulting service. There are no exams nor credits.

Contact: beratung@stat.math.ethz.ch . Tel. 044 632 2223. See also http://stat.ethz.ch/consulting

Requirements: Knowledge of the basic concepts of statistics is desirable.
401-0625-01LApplied Analysis of Variance and Experimental Design Information 5 credits2V + 1UL. Meier
AbstractPrinciples of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
ObjectiveParticipants will be able to plan and analyze efficient experiments in the fields of natural sciences. They will gain practical experience by using the software R.
ContentPrinciples of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
LiteratureG. Oehlert: A First Course in Design and Analysis of Experiments, W.H. Freeman and Company, New York, 2000.
Prerequisites / NoticeThe exercises, but also the classes will be based on procedures from the freely available, open-source statistical software R, for which an introduction will be held.
401-5640-00LZüKoSt: Seminar on Applied Statistics Information 0 credits1KM. Kalisch, A. Bandeira, P. L. Bühlmann, R. Furrer, L. Held, T. Hothorn, M. H. Maathuis, M. Mächler, L. Meier, M. Robinson, C. Strobl, C. Uhler, S. van de Geer
AbstractAbout 5 talks on applied statistics.
ObjectiveSee how statistical methods are applied in practice.
ContentThere will be about 5 talks on how statistical methods are applied in practice.
Prerequisites / NoticeThis 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.
447-0625-01LApplied Analysis of Variance and Experimental Design I Restricted registration - show details
Only for DAS and CAS in Applied Statistics.
3 credits1V + 1UL. Meier
AbstractPrinciples of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs.
ObjectiveParticipants will be able to plan and analyze efficient experiments in the fields of natural sciences. They will gain practical experience by using the software R.
LiteratureG. Oehlert: A First Course in Design and Analysis of Experiments, W.H. Freeman and Company, New York, 2000.
447-0625-02LApplied Analysis of Variance and Experimental Design II Restricted registration - show details
Only for DAS and CAS in Applied Statistics.
3 credits1V + 1UL. Meier
AbstractRandom effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
ObjectiveParticipants will be able to plan and analyze sophisticated experiments in the fields of natural sciences. They will gain practical experience by using the software R.
LiteratureG. Oehlert: A First Course in Design and Analysis of Experiments, W.H. Freeman and Company, New York, 2000.
447-0990-00LWorkshop Restricted registration - show details
Only for DAS in Applied Statistics.
1 credit1SL. Meier
AbstractIn the workshop each participant gives a short talk about a recent statistical problem encountered in their daily work.
ObjectivePresentation of a statistical problem, getting to know different applications of statistical methodology.
447-6201-00LNonparametric and Resampling Methods Restricted registration - show details
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.
2 credits2GL. Meier, D. Kuonen
AbstractNonparametric tests, randomization tests, jackknife and bootstrap, as well as asymptotic properties of estimators.
ObjectiveFor classical parametric models there exist optimal statistical estimators and test statistics whose distributions can often be determined exactly. The methods covered in this course allow for finding statistical procedures for more general models and to derive exact or approximate distributions of complicated estimators and test statistics.
ContentNonparametric tests, randomization tests, jackknife and bootstrap, as well as asymptotic properties of estimators.
Prerequisites / NoticeThis course is part of the programme for the certificate and diploma in Advanced Studies in Applied Statistics. It is given every second year in the winter semester break.