300198 Multivariate Analyses (engl.) (S) (WiSe 2013/2014)

This course will be conducted in English.
Descriptive statistical parameters such as frequency distributions, means, cross-tabs and correlations are sometimes sufficient to describe narrowly defined specific aspects of a research topic and to analyze simple relationships. In contrast, multivariate analysis methods are always used to investigate more complex empirical and theoretical relations. Further, they enable to discover unknown structures in the analyzed data to verify theoretical hypothesized structures. This course introduces in various multivariate techniques (factor analysis, variance analysis, regression analysis, discriminant analysis, cluster analysis) and applies them on actual empirical data. At this, the focus is on the practical application of the methods, their possibilities and restrictions as well as the interpretation of their results. Their mathematical basics are only considered to the extent necessary for the understanding of these methods.

scheduled work form:
Group and plenary work.

Learning outcomes and competences:
Students gain a basic but also critical understanding of these methods and the corresponding basic skills to apply these methods.

Requirements for participation, required level

basic knowledge in statistics and methods of empirical research

Bibliography

Stevens, J. P. (2009): Applied multivariate statistics for the social sciences. 5th edition. New York.

Tabachnick, B. G.; Fidell, L. S. (2007): Using multivariate statistics. 5th edition. Boston.

Wonnacott, T. H.; Wonnacott, R. J. (1990): Introductory statistics. 5th edition. New York.

Wonnacott, R. J.; Wonnacott, T. H. (1979): Econometrics. New York.