Advanced Statistical Methods


Aims

Being able to apply the selected advanced statistical methods in practical situations, and being able to interpret the results. Being able to use the R language for running the selected statistical methods.

Information

This course builds on the Statistical Methods course. It extends to more advanced statistical multivariate analysis techniques and their application in business and economics. A selection of the following techniques will be treated: confirmatory factor analysis, structural equations models (Lisrel), generalized linear models, multilevel methods, social network analysis, support vector machines, correspondence analysis, and unfolding. Much attention is given to the application in practical situations and the interpretation of the techniques in empirical research in economics and business. Students apply the techniques using the statistical language R. It is assumed that the students have followed the Statistical Methods course.

Materials

• Kuhnert, P. and Venables, B. (2005). An Introduction to R: Software for Statistical Modelling & Computing. CSIRO Mathematical and Information Sciences. Cleveland, Australia.
• Selected chapters of Lattin, J., Carroll, J.D. & Green, P.E. (2003), Analyzing Multivariate Data, Brooks/Cole, Thompson Learning.
• Selected papers.

Additional info

Prerequisite for this course is BERMMC004 Statistical Methods. It is advised that students bring their laptop and have the R language installed. R can be downloaded for free via http://www.r-project.org/ (download from CRAN). It is also recommended to install R-Studio from http://rstudio.org/