ABSTRACT
Multivariate analysis deals with the analysis of research problems that involve more than two variables. The popularity of multivariate techniques has increased with the advent of advanced computing resources, and the availability of off-the shelf statistical software packages, which made the application of multivariate techniques easier. Multivariate techniques can be categorized as dependency techniques and Interdependency techniques. Multiple regression analysis analyzes the linear relationship between a dependent variable and multiple independent variables. Similar to the coefficient of determination used in bivariate regression analysis, the coefficient of multiple determination measures the magnitude of the association of the variables involved in multiple regression. Multicollinearity makes it difficult for researchers to ascertain which of the independent variables influence the dependent variable. Discriminant analysis is a technique used for classifying a set of observations into predefined groups based on a set of variables known as predictors of input variables.
