Dates
| weekly | Tuesday | 14:15 - 15:45 | 12.10.2026 - 29.01.2027 | C 3.120 Seminarraum | Start 1. lecture week |
Curriculum context
Resit date: : Keine selbständige Anmeldung zum Wiederholungstermin möglich. info_outline
Tuesday, 23.03.2027, 12:15, room C HS 3, C HS 4
Präsenzklausur
Organizational information
Registration
Registration does not begin until 02.10.2026 at 08:00. It ends on 12.10.2026 at 23:59.
The registration is restricted to the following fields or courses of study:
- Leuphana Bachelor / Major Economics / alle Semester
- Leuphana Bachelor / Major Studium Individuale / alle Semester
- Leuphana Bachelor / Minor Studium Individuale / alle Semester
Persons
Content
This course provides an overview of regression analysis. It centres around the question of how to identify causal effects from linear regression models that are estimated using the ordinary least squares (OLS) estimator. The main focus is to discuss the estimation of causal effects under mild identifying assumptions rather than the properties of the OLS estimator under ideal conditions that are of little practical relevance.
Contents:
1. About this course
2. The simple linear regression model
3. Inference in the simple linear regression model
4. The multiple linear regression model
5. Inference in the multiple linear regression model
6. Nonlinear regression functions
7. The validity of regression analyses
Students not only learn how to apply OLS regression appropriately, but also learn how to assess and scrutinise empirical analyses that use it and about its strengths and weaknesses. Moreover, students acquire the relevant skills to use OLS regression in own empirical analyses, e.g. in later empirical research projects or in their bachelor thesis.
Successful completion of the courses Mathematics I/II and Statistics I/II
Evaluation
Further information on teaching evaluation: https://www.leuphana.de/en/teaching/quality-management/evaluation/course-evaluation.html