Registration ends 07.4.2026 at 23:59 h

In the beginning, the course addresses and recapitulates the fundamental multi-variate techniques (e.g., ANCOVA, multiple and logistic regression, repeated Measures ANOVA). Beyond that, the course focuses on data that is informative for answering questions of sustainability, but that can often not be derived from experiments. Instead, one often needs to rely on sources from field research or pre-existing records. Moreover, such data usually has a temporal dimension, and is multidimensional. In this course, students will first be provided with an overview of current data analysis techniques suitable for the analysis of multidimensional data, and data with a time component. Then, a selected group of analysis techniques will be presented in detail. The mathematical foundations of these analysis techniques will be introduced, and the techniques will be applied to data sets from sustainability science and psychology.

Students will acquire expertise in selected multi-factorial and multivariate analysis techniques (e.g., ANCOVA, multiple and logistic regression, with moderator analysis, structural equation modelling) and/or time series data, check whether the assumptions of these techniques are met, and interpret the results of these analyses. They will develop the skill to implement different multivariate and time series analysis procedures in R.

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