Allgemeine Informationen
| Untertitel | |
| Veranstaltungsnummer | 35621 |
| Semester | WiSe 23/24 |
| Aktuelle Anzahl der Teilnehmenden | 90 |
| Heimat-Einrichtung | Lehreinheit für Computergestützte Statistik und Mathematik |
| beteiligte Einrichtungen | Graduiertenzentrum, Lehrstuhl für Statistik und Data Analytics |
| Veranstaltungstyp | Vorlesung in der Kategorie Lehre (mit Prüfung) |
| Erster Termin | Di., 17.10.2023 10:00 - 12:00 Uhr |
| Art/Form | online |
| Voraussetzungen |
The course aims at students with a basic knowledge in statistics and complements some of the topics treated in 'Methods in Econometrics I and II'. |
| Lernorganisation |
Guided computer tutorials; students are expected to deepen their knowledge by completing self-contained R-exercises and by presenting/explaining code snippets. |
| Leistungsnachweis |
Final exam (60 minutes); R-skills are certified via a certificate when the final exam is passed. |
| SWS |
2 |
| Literatur |
|
| Qualifikationsziele |
The course focuses on estimating and evaluating regression models with the statistical software R. Model evaluation procedures discussed in class range from graphical methods, classic validation techniques and tests to simulation-based approaches. The course includes model selection (i.e., finding the best model from a large number of possible models), model validation (i.e., checking whether the presumed best specification satisfies the model assumptions), and model interpretation (for linearly and/or nonlinearly transformed variables). Additionally, different data structures such as cross-sections, time series, and panel data are shortly discussed. |
| Workload |
2 SWS (30 h attendance, 45-60 h self-study) |
| Sonstiges |
Course is taught in English. |
| ECTS-Punkte |
3 |
