| Lerninhalte |
This project seminar is designed for students who want to learn more about the use of statistical- and machine learning methods in the empirical social sciences. Topics covered include
- resampling methods (bootstrap, cross-validation, permutation tests)
- regularized regression
- tree-based methods (regression trees, classification trees)
- ensemble methods (bagging, random forests, boosting)
The course will be taught as a combination of class meetings, practical R Studio demonstrations and flipped classroom assignments. It is open to both psychology students as part of their two-semester master project seminar (the project seminar assignment can be continued during the winter semester) and interested PhD students who want to take a one-semester introductory course on statistical learning methods. |
