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Zurich R Courses (Introductory and advanced courses)

Introductory and advanced courses on statistical dataanalysis with the open-source software R


English/German (depending on the composition of the participants)




Confirmation of participation


Beginners as well as advanced users of all professional groups, who wish to use R academically or non-academically for research, teaching, and practical data analysis.



Universität Zürich, Psychologisches Institut
Psychologische Methodenlehre, Evaluation und Statistik
Prof. Dr. Carolin Strobl
Binzmühlestrasse 14, Box 27, 8050 Zürich



R is a software environment for statistical analysis that enables users to conduct both simple and complex data analyses reproducibly and transparently. In addition to the most common statistical analysis methods and graphics, which are also available in commercial packages such as SPSS, R also provides a wide range of more specialized methods in the form of add-on packages.
Unlike commercial products, R is a free open-source software that is continuously being improved and extended by a large circle of international statistics experts.
R is based on a flexible programming environment, and thus also allows users to implement their own functions and to conduct simulation studies.
R is used at universities with great success in both research and teaching, and more and more companies are discovering the potential of R for their data analyses.
The Zurich R Courses offer a platform for established and experienced lecturers of UZH and ETH as well as invited international experts, who explain the application of R and its statistical background in a way that is understandable and applicable in practice.

Introduction to R
Courses of this category are aimed at R beginners who have basic knowledge in statistics. They provide an introduction to the application of R in an understandable and practically oriented manner.

Statistical data analysis with R
Courses of this category are aimed at users who have basic knowledge in statistics and have used R before. They cover a general introduction as well as the practical application of particular statistical methods in R, e.g.:
‒mixed (hierarchical) models with R
‒structural equation models with R
‒machine learning methods with R



Courses see above