In this module component, students will learn about and practice:
- Students are able to run a multiple regression analysis with 1 dependent ratio variable and 2 or more independent ratio or categorical variables with more than 2 categories.
- Students are able to study and interpret interaction effects between two independent variables.
- Students are able to check the assumptions of linear regression and are able to use nonparametric alternatives in case assumptions are not met (Kruskal-Wallis, Spearman and Kendall).
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This Data Analysis component expands the linear model from the course Data Analysis 1. The study unit discusses analysis of variance within the unifying linear model framework, assumptions of the linear model, moderation, and non-parametric tests. The software used is “R for statistics”.
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