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# 105.596 Econometrics 1: Linear Models This course is in all assigned curricula part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_1y",{id:"j_id_1y",showEffect:"fade",hideEffect:"fade",target:"isAllSteop"});});This course is in at least 1 assigned curriculum part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_20",{id:"j_id_20",showEffect:"fade",hideEffect:"fade",target:"isAnySteop"});});

2018W, VO, 2.0h, 3.0EC

## Properties

• Semester hours: 2.0
• Credits: 3.0
• Type: VO Lecture

## Aim of course

Understanding of basic econometric methods: linear regression models, including estimation and inference.

## Subject of course

Simple and multiple linear regressions model, least-squares estimation, geometric interpretation, Frisch-Waugh, coefficient of determination, classical linear regression model, Gauss-Markov theorem, variance estimation, testen linear hypotheses, generalized linear regression model, Aitken estimator, asymptotic analysis.

## Course dates

DayTimeDateLocationDescription
Tue14:00 - 15:1502.10.2018FH Hörsaal 7 Econometrics 1: Linear Models

Not necessary

## Literature

• Schönfeld: Methoden der Ökonometrie, Band I, 1969.
• Ruud: An Introduction to Classical Econometric Theory,  2000.
• Auer, Ökonometrie: Eine Einführung, 2013.
• Gross: Linear Regression, 2003.
• Kleiber & Zeileis: Applied Econometrics with R, 2008.

## Previous knowledge

Basic knowledge of linear algebra, probability theory and statistics.

German