Computational Statistics - Regression in R
35621
Vorlesung:
Computational Statistics - Regression in R
(WiSe 24/25)
Course times
Di. 10:00 - 12:00 (wöchentlich)
Course venue
nicht angegeben
Start date
Dienstag, 15.10.2024 10:00 - 12:00 Uhr
Teaching contact hours per week
2
Description
The course focuses on estimating regression models and evaluating the estimated specifications 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 effects of variables being measured on different scales and variable transformations are discussed. Dealing with different data structures such as cross-sections, time series, and panel data is also covered in class.
Pre-requisites
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'.
Mode of study
Guided computer tutorials; students are expected to deepen their knowledge by completing self-contained R-exercises and by presenting/explaining code snippets.
Assessments
Final exam (60 minutes); R-skills are certified via a certificate when the final exam is passed.
Indicative reading list
- Kleiber, C. & A. Zeileis (2008), Applied Econometrics with R, Springer.
- Field, A. & Miles, J. & Field, Z. (2012), Discovering Statistics using R, SAGE.
- Wooldridge, J. (2013), Introductory Econometrics, 5Ed., South Western.
- Greene, W.H. (2012), Econometric Analysis, Pearson.
- Ligges, U. (2008), Programmieren mit R, Springer.
Additional information
Course is taught in English.
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