Multivariate Statistics In Psychology
This module introduces students to the use of multivariate methods for the analysis of psychological data. Included among the methods to be covered may be canonical correlation, discriminant function analysis, multivariate analysis of variance, exploratory and confirmatory factor analysis, and structural equation modelling. Emphasis will be placed on the development of skills for multivariate data analysis through hands-on analysis and interpretation of datasets.
Modular Credits: 4
Workload: 0-3-0-5-2
Pre-requisite(s): PL2101Y/PL2131 and PL2132, or consent of instructor
Preclusion(s): PL4204
Cross-listing(s): Nil
Workload Components: A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial/seminar hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc. per week
E: no. of hours for preparatory work by a student per week