In this chapter, we consider multiple regression models as a method for modeling multiple observed variables. Multiple regression, a general linear modeling approach to the analysis of data, has become increasingly popular since 1967 (Bashaw & Findley, 1968). In fact, it has become recognized as an approach that bridges the gap between correlation and analysis of variance in answering research hypotheses (McNeil, Kelly, & McNeil, 1975). Many statistical textbooks elaborate the relationship between multiple regression and analysis of variance (Draper & Smith, 1966; Edwards, 1979; Hinkle, Wiersma, & Jurs, 2003; Lomax, 2007).