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
course contents
• 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
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
2
name of lecturer(s)
Prof. (FH) Dr. Peter Dietrich
course unit code
05.MV.RSM.2
type of course unit
integrated lecture
mode of delivery
Compulsory
work placement(s)
none