Advanced Market Research (WiSe 2022/23)
|Monday||12:00- 14:00||weekly||10.10.2022- 21.11.2022||Schlossplatz 46, H 3|
|Wednesday||08:00- 14:00||weekly||12.10.2022- 23.11.2022|
|Thursday||12:00- 14:00||weekly||13.10.2022- 24.11.2022||Juridicum, JUR 4|
This course takes place in the first term of the winter semester.
Every Monday we have a plenary session to discuss a specific method covered in the course.
Coaching sessions will take place in person every Wednesday between 8:00 hrs and 14:00 hrs. These coaching sessions are group meetings and will be coordinated with the coaching sessions of the course 'Market-oriented Leadership'.
The sessions on Thursday are planned for individual consultation appointments (please check course schedule on Learnweb for exceptions).
Examination: Group work (33 %) | Final exam (67 %). Please register at the examination office for the early examination period.
ECTS: 6 (PO BWL 2010)
During the course, please communicate and stay updated via the course page on Learnweb. Announcements, lecture slides and any additional material will be published there.
Background and relations to other courses:
This course teaches basic methods of multivariate data analysis that enable students to answer empirical research questions in marketing. The various methods will be applied to a marketing research project to enhance the learning experience. The methods discussed are the basis for machine learning methods. Knowledge of these methods is essential for marketing managers in a data-driven world.
- Analysis of variance
- Regression analysis
- Logistic regression
- Factor analysis
- Cluster analysis
- Conjoint analysis
It is the objective of this course that students learn how to apply the different methods in a competent manner, and how to derive managerial insights based on the results of empirical research.
Backhaus, Erichson, Gensler, Weiber, and Weiber (2021). Multivariate Analysis - An Application-Oriented Introduction, Springer Gabler Wiesbaden, DOI: https://doi.org/10.1007/978-3-658-32589-3.
- apl. Professor Dr. Sonja Gensler (responsible)
- Lisa Richter (accompanying)
- Fabienne Michel-Angeli (accompanying)
- Stefanie Dewender (accompanying)