STA3104 Multivariate Statistical Analysis

This course unit is intended to inculcate into learners the skills for analyzing data sets that have several variables as required by many social economic surveys. It covers the description of     what is entailed in multivariate data and provides some flash back on matrix algebra to enable learners appreciate the link between matrix algebra and multivariate statistics.  Covered also are; Descriptive Multivariate Statistics, Multivariate Distribution Theory, Multivariate Inference, Multiple Regression Analysis, Multivariate Analysis of Variance (MANOVA), Principle Component Analysis, Cluster Analysis and Factor Analysis.

General Course Objectives
By the end of this course, learners will be able to:

• Describe multivariate statistics
• Perform a PCA on a software
• Calculate regression coefficients
• Perform factor analysis on a given data set

Expected Learning Outcomes 

• This course unit aims at introducing learners to the main ideas of how to analyze data sets that have several variables.