STA347 Multivariate Statistical Analysis (8)
CSU Discipline Area: Mathematics and Statistics (MASTA)
Duration: One session
Abstract:
This subject introduces students to multivariate modelling through an applied approach to data analysis. The emphasis will be on demonstration of techniques and their applicability via empirical investigations of the various methodologies. Topics include: principal components analysis, canonical correlation, discriminant analysis, multivariate analysis of variance, factor analysis, cluster analysis, conjoint analysis and multidimensional scaling.
+ Subject Availability Modes and Locations
No offerings have been identified for this subject in 2013.Continuing students should consult the SAL for current offering details prior to contacting their course coordinator: STA347
Where differences exist between the handbook and the SAL, the SAL should be taken as containing the correct subject offering details.
Prerequisite(s):
Objectives:
Upon successful completion of this subject, students should:
Be able to classify given problems by their appropriate analysis technique;
Be able to apply the chosen technique to the solution of the problem;
Be able to report and explain the results of the analysis.
Syllabus:
The subject will cover the following topics:
Review of multiple linear regression (MLR) and the analysis of variance (ANOVA); Introduction to multivariate models by examples; Principal components analysis: dimensionlity reduction, handling multicollinearity; Canonical correlation; Discriminant analysis; Multivariate analysis of variance (MANOVA); Factor analysis; Cluster analysis; Conjoint analysis; Multidimensional scaling.
Residential School
This subject contains a optional 2 day residential school.
The information contained in the 2013 CSU Handbook was accurate at the date of publication: 24 April 2013. The University reserves the right to vary the information at any time without notice.