Advanced Market Research (WiSe 2023/24)


Course Number
044230

Field(s) of Study
Master

University Calendar
This course in the LSF-Portal

Learnweb Platform
This course in Learnweb

Type
Lecture/Exercise

Course Language
englisch

Course schedule

Day Time Frequency Date Room
Monday 12:00- 14:00 weekly 09.10.2023- 20.11.2023 Schloss, S 9
Wednesday 08:00- 14:00 weekly 11.10.2023- 22.11.2023  
Thursday 12:00- 14:00 weekly 12.10.2023- 23.11.2023 Juridicum, JUR 4

Notice

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 (30 minutes per group).

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

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.

Description

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.



Main topics:

  • Analysis of variance
  • Regression analysis
  • Logistic regression
  • Factor analysis
  • Cluster analysis
  • Conjoint analysis 

 

Course objective:

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.

Literature

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.

Lecturers

  • apl. Professor Dr. Sonja Gensler (responsible)
  • Lisa Richter (accompanying)
  • Fabienne Michel-Angeli (accompanying)
  • Stefanie Dewender (accompanying)