MRES 502 Multivariate Statistics Select Term:
This course covers the basic multivariate techniques that are currently used in various areas of social sciences. The learning goal for students is to have a conceptual understanding of each statistical technique, be able to apply the correct technique to any given set of data, properly interpret the output of statistical computer packages, and understand and critique scientific papers that use these techniques. The course begins with an introductory session on matrix algebra, sample geometry and random sampling. Next, the properties of the multivariate normal distribution are examined with an emphasis on how to make inferences about multivariate means and to compare several multivariate means (MANOVA). Other topics that are covered include analysis of covariance structures including principal components, factor analysis and canonical correlation analysis as well as classification and grouping techniques such as discriminant analysis, clustering and multidimensional scaling.
SU Credits : 3
ECTS Credit : 6
Prerequisite : -
Corequisite : -