Logistic Regression and Discriminant Analysis

This chapter provides an overview of Logistic Regression and Discriminant Analysis . Logistic regression and discriminant analysis, like multiple regression, are useful when you want to predict an outcome or dependent variable from a set of predictor variables. They are similar to linear regression in many ways. However, logistic regression and discriminant analysis are more appropriate when the dependent variable is categorical. This chapter helps the reader know when to do these and related methods, understand the assumptions and requirements of these methods, and understand how to perform and interpret each of them using SPSS. Multinomial logistic regression is used when the dependent/outcome variable has more than two categories, but it is beyond the scope of this chapter.