Research Methods III: Advanced Quantitative Analysis
level of course unit
2nd study cycle, Master
Learning 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.
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
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)
assessment methods and criteria
Online tasks, term paper, exam
language of instruction
English
number of ECTS credits allocated
4
eLearning quota in percent
25
course-hours-per-week (chw)
2
planned learning activities and teaching methods
Blended Learning
semester/trimester when the course unit is delivered
3
name of lecturer(s)
Prof. (FH) Dr. Peter Dietrich
course unit code
06.MV.RSM.3
type of course unit
integrated lecture
mode of delivery
Compulsory
work placement(s)
none