Zurich R Courses (Introductory and advanced courses)

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

Study Structure English/German (depending on the composition of the participants)
Duration 1–2-Day-Courses
Degree Confirmation of participation
Target Audience 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.
Website www.zhrcourses.uzh.ch
Information Universität Zürich, Psychologisches Institut
Psychologische Methodenlehre, Evaluation und Statistik
Prof. Dr. Carolin Strobl
Binzmühlestrasse 14, Box 27, 8050 Zürich
E-mail zhRcourses@psychologie.uzh.ch
Description 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.
Introduction to R: 13./14.9.2018

Special: Introduction to R for the Life Sciences - An R4All Course Series
Courses of this category are aimed at R beginners particularly from the life sciences. They provide an introduction to the application of R in an understandable and practically oriented manner and are specifically tailored to the needs and prerequisites of the life sciences.
R4All: An introduction to the basics of R: on request
R4All: Building on the basics of R: 6./7.9.2018

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
Shiny and Interactive Visualisation in R: 5.9.2018
Bayesian inference using R-INLA: 29./30.10.2018
Data Processing, Visualisation, and Reporting using R: 29./30.11.2018
lavaan: latent variable modeling in R: 28./29.3.2019
Mixed (hierarchical) Models in R: on request
Categorical Data Analysis with R: on request
Missing Value Imputation: on request
Introduction to classification and regression trees, random forests and model-based recursive partitioning in R: on request

Programming with R
Courses of this category are aimed at advanced R users and provide special knowledge, ranging from basic programming commands to building your own R packages.
Introduction to Programming with R: on request
Higher-Performance R Programming via C++ Extensions: on request
Courses 2018 (see above)