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Econometrics II (Quantitative Research Methods)

level of course unit

Advanced

Learning outcomes of course unit

Students will
master important fundamental methods of quantitative data analysis
be able to carry out this analysis with the help of a computer
be able to apply their knowledge to real-world problems.

prerequisites and co-requisites

EC1

course contents

The goal of this course is for students to master the fundamental quantitative and qualitative methods of data analysis, which are dependent on the quality of available data in the context of a business and, in particular, their applications in marketing and market research questions. These include regression analysis, analysis of variance, discrimination analysis, contingency analysis, factor analysis, cluster analysis, multidimensional scaling as well as conjoint analysis. The application of these methods will be based on real data and carried out on a computer with standard statistical software packages (e.g. SPSS, Stata, EViews, Gauss).

recommended or required reading

Kennedy, P.: A Guide to Econometrics. 5. Aufl. Blackwell, 2006.
Wooldridge, J.M.: Introductory Econometrics. A Modern Approach. 2. Aufl., Mason, 2003.

assessment methods and criteria

Written exam and/or scientific paper and/or presentation

language of instruction

English

number of ECTS credits allocated

3

planned learning activities and teaching methods

Lecture, group work, presentation and task discussion

semester/trimester when the course unit is delivered

2

name of lecturer(s)

Dr. Gruber Stefan

year of study

1st year

recommended optional program components

not specified

course unit code

V.EC2.1

type of course unit

compulsory

mode of delivery

In-class course

work placement(s)

not applicable