This course aims to develop an understanding of and practical skills in choosing appropriate strategies and analytic procedures to manage, analyze, present, interpret and report multivariate data collected in and arising from psychological research.  The training will be focused on the multivariate statistics commonly used in psychology research, including MANOVA, multiple regression, path analysis, factor analysis (EFA and CFA), and structural equation modeling (SEM). Other topics such as missing data, logistic regression, etc will also be introduced.

Upon completion of this course, students will be capable of doing in-depth data analysis independently for their research (e.g., final year thesis). In this course, students are given plenty of practice and exercise with the statistical softwares (e.g., SPSS, LISREL, etc). Mathematical calculations will be kept to a minimal level. Knowledge about elementary statistics such as correlation, ANOVA, and regression will be advantageous.