ABSTRACT
This chapter aims to render the information in Cohen et al, more accessible to novice to intermediate users of MRA and provides directions on how to run MRA using SPSS. Multiple regression analysis (MRA) refers to a group of correlation-based statistical techniques that examines the relationship between a criterion variable and multiple predictor variables. The primary purpose of MRA is to generate a linear or a nonlinear equation that creates a line that fits the data well while ideally achieving parsimony in the model. MRA is a family of several different types of analyses such as standard regression analysis, hierarchical regression analysis, and stepwise regression analysis. To check multicollinearity assumption, run a simple bivariate correlation analysis using CV and all PVs under investigation. Prior to main analyses, the researcher must first make sure that the data meet the assumptions of multivariate analyses such as MRA that is data screening, transform the data if they do not meet the assumptions.
