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Research Methods III: Advanced Quantitative Analysis
level of course unit
2nd study cycle, MasterLearning outcomes of course unit
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 and co-requisites
Course: Research Methods I & II
course contents
• 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 or required reading
• 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 of instruction
Englishnumber of ECTS credits allocated
4eLearning quota in percent
25course-hours-per-week (chw)
2planned learning activities and teaching methods
Blended Learning
