Linear probability functions are briefly discussed. The theory of linear discriminant functions in the two-class case is then presented. Such a function, which is a linear combination of observed variables, is used to classify each observed item into one of two classes. Certain identities between the two types of functions are obtained. Whereas the results from the two different models are the same, their distributional assumptions and derivations are quite different.