Statistical Methods


Aims

  • Gain insights in the most important multivariate statistical techniques;
  • Obtain skills in implementing these techniques using SPSS or R;
  • Being able to select an appropriate multivariate technique, apply it sensibly to empirical data, and write a short report about it.

Information

In this course, students learn to apply several statistical multivariate analysis techniques and their application in business and economics. Among the techniques to be treated are multiple regression, analysis of variance, classical test theory (including Cronbach’s alpha), exploratory factor analysis, cluster analysis, (multinomial) logistic regression, and multidimensional scaling.

 

Emphasis in this course lies on understanding what statistical technique to use, when to use it, and how to use it given a practical research question. Students are encouraged to bring their own data sets and apply the techniques to these data. Through assignments on empirical data sets (either provided by the student or by the teachers) and by using mostly SPSS software students are trained in using the techniques. It is assumed that the students have followed a basic course in statistics.

Assessment

During this course, each week a group assignments need to be   made. To pass this course, an individual final assignment should be made.

Materials

Selected chapters of Lattin, J., Carroll, J.D. & Green, P.E. (2003), Analyzing Multivariate Data, Brooks/Cole, Thompson Learning and selected readings that will provided during the course.