Research Methods III: Advanced Quantitative Analysis
Niveau
2nd study cycle, Master
Learning outcomes of the courses/module
The students are able to:
• explain the limitations of linear models such as OLS with respect to nominal/ordinally-scaled dependent variables and identify alternative models.
• identify the potentials of models with binary dependent variables and apply them competently to relevant research questions.
• analyze questions from market research with regard to e.g. purchase decisions or customer satisfaction using Logit/Probit models and to interpret the results.
• theoretically model consumer preferences and optimal pricing through conjoint analysis and investigate them empirically.
• implement and evaluate models from the field of nominal/ordinal scaled dependent variables and conjoint analysis independently on the basis of software such as STATA or R.
• explain the limitations of linear models such as OLS with respect to nominal/ordinally-scaled dependent variables and identify alternative models.
• identify the potentials of models with binary dependent variables and apply them competently to relevant research questions.
• analyze questions from market research with regard to e.g. purchase decisions or customer satisfaction using Logit/Probit models and to interpret the results.
• theoretically model consumer preferences and optimal pricing through conjoint analysis and investigate them empirically.
• implement and evaluate models from the field of nominal/ordinal scaled dependent variables and conjoint analysis independently on the basis of software such as STATA or R.
Prerequisites for the course
Course: Research Methods I & II
Course content
• Analysis of nominal/ordinal scaled dependent variables
• Logit/Probit models and Maximum Likelihood Estimation
• Empirical preference estimation and conjoint analysis
• Determinants of purchase decision and customer satisfaction
• Implementation of models with STATA or R
• Logit/Probit models and Maximum Likelihood Estimation
• Empirical preference estimation and conjoint analysis
• Determinants of purchase decision and customer satisfaction
• Implementation of models with STATA or R
Recommended specialist literature
• Wooldridge, Jeffrey: Introductory Econometrics A Modern Approach. Cenage Learning (latest edition)
• Chapman, Chris; McDonnell Feit, Elea: R For Marketing Research and Analytics. Springer (latest edition)
• Orme, Bryan: Getting Started with Conjoint Analysis. Research Publishers (latest edition)
• Chapman, Chris; McDonnell Feit, Elea: R For Marketing Research and Analytics. Springer (latest edition)
• Orme, Bryan: Getting Started with Conjoint Analysis. Research Publishers (latest edition)
Assessment methods and criteria
Online tasks, term paper, exam
Language
English
Number of ECTS credits awarded
4
Share of e-learning in %
25
Semester hours per week
2.0
Planned teaching and learning method
Blended Learning
Semester/trimester in which the course/module is offered
3
Name of lecturer
Prof. (FH) Dr. Peter Dietrich
Academic year
Key figure of the course/module
06.MV.RSM.3
Type of course/module
integrated lecture
Type of course
Compulsory
Internship(s)
none