Different Aspects of Regression Analysis
Lecture: Dr. Andreas Groll
Date and Time
- Lectures: Tue 12:0 to 13:30 (Quant Lab, Room B 120), Wed 10:15 to 11:45 (every two weeks) (Quant Lab, Room B 120).
- Exercises: Wed 10:15 to 11:45 (every other week) (Quant Lab, Room B 120).
- Contents: Regression analysis is one of the most used statistical methods for the analysis of empirical problems in econonimc, social and other sciences. A variety of model classes and inference concepts exists, reaching from the classical linear regression to modern non- and semiparamtric regression. The aim of this course is to give an overview of the most important concepts of regression and to give an impression of its flexibility.
The following main topics will be covered:
- Linear regression models
- Random effects models (mixed models)
- Time series analysis
- Generalized linear models
Note that - depending on the audience - this course might be taught in English.
- The lectures adresses: Studierende des Bachelorstudiengangs Wirtschaftsmathematik
- Required previous knowledge: Stochastik; Kenntnisse aus der Wahrscheinlichkeitstheorie empfehlenswert
- Leistungsnachweis: Gilt für Bachelorprüfung Wirtschaftsmathematik (WP13).
 Fahrmeir, L., T. Kneib, and S. Lang (2007). Regression. Berlin: Springer.
 Fahrmeir, L. and G. Tutz (2001). Multivariate Statistical Modelling Based on Generalized Linear Models (2nd ed.). New York: Springer.
 J. D. Hamilton (1994). Time Series Analysis. Princeton University Press.
Further literature will be announced in the course.
Notes (PDF, 2.2MB)
Problem and Answer Sheets
The exam will take place on Tuesday, 29.01.2013, in Room B120 (Quant Lab) from 12:00-13:30.
The result of the exam can be found here: Exam Results (PDF, 41.6KB)