ABSTRACT
This chapter outlines some of the major uses of regression methodology. Data analysis of any kind, including a regression analysis, has the potential for far-reaching consequences. Regression analysis consists of graphic and analytic methods for exploring relationships between one variable, referred to as a response variable, and one or more other variables, called predictor variables. Regression analysis is distinguished from other types of statistical analyses in that the goal is to express the response variable as a function of the predictor variables. Regression analysis can aid in the confirmation or refutation of a causal model, but the model itself must be conceived by theoretical considerations. Correlation analysis is called for if one desires to assess the simultaneous variability of a collection of variables. Model specification is critically important in regression analyses whose objective is the assessment of the relative value of individual predictor variables on the prediction of the response.
