Research Methods II: Quantitative Analysis
level of course unit
2nd study cycle, Master
Learning outcomes of course unit
The students are able to:
• distinguish causality from correlation and design empirical analyses accordingly.
• implement and interpret multivariate methods of regression analysis.
• transfer research questions from business practice into a model framework and test them by hypothesis formation.
• explain the standard model of OLS regression and critically reflect limitations / potentials of results.
• use statistical software such as STATA or R to independently implement empirical analyses.
prerequisites and co-requisites
Course Research Methods I
• Multivariate methods and OLS regression
• Estimation of coefficients with hypothesis tests
• Interpretation of indicators for goodness of fit model
• Multicollinearity and heteroskedasty
• Statistical software like STATA or R
recommended or required reading
• Wooldridge, Jeffrey: Introductory Econometrics A Modern Approach. Cengage Learning (latest edition)
• Heiss, Florian: Using R for Introductory Econometrics. CreateSpace Independent Publishing Platform (latest edition)
• Stock, James; Watson, Mark: Introduction to Econometrics. Pearson Education Limited (latest edition)
assessment methods and criteria
Online tasks, term paper, exam
language of instruction
number of ECTS credits allocated
eLearning quota in percent
planned learning activities and teaching methods
semester/trimester when the course unit is delivered
name of lecturer(s)
Prof. (FH) Dr. Peter Dietrich
course unit code
type of course unit
mode of delivery