Multivariate Statistics 1
In this course you will learn when and how to apply unsupervised learning methods such as PCA for dimension reduction and k-means, hierarchical clustering or some hybrid approaches for clustering. It also covers some rotation techniques after dimensionality reduction as well as well as mixture models and heatmaps (clustering).
The course will help to understand the basis of the theory when doing a multivariate analysis. All topics are accompanied with hands-on exercises using the statistical software R. The participants are invited to ask as many questions as they want about the analyses on their own dataset.
Voraussetzung: Programmierungserfahrung mit R
Mehr Informationen erhalten Sie hier!
- 16 March 2023, 09:00 - 17:00
- 17 March 2023, 09:00 - 12:30
- 23 March 2023, 09:00 - 17:00
- 24 March 2023, 09:00 - 17:00