Publisher Summary This chapter introduces the use of the regression model to make inferences on means of populations identified by specified values of one or more quantitative factor variables. It discusses the uses of the linear regression model and explains the procedures for the estimation of the parameters of that model and the subsequent inferences about those parameters. It provides an introduction to diagnosing possible difficulties in implementing the model, along with giving some hints on computer usage and discussing inferences for the response variable. It also presents the related concept of correlation and discusses the information and formulas necessary to obtain the regression parameter estimates by using a handheld calculator. A regression analysis starts with an estimate of the population mean(s) using a mathematical formula, called a “function,” which explains the relationship between the predictor variable(s) and the response variable. This function is called the “regression model” or “regression function.” In simple linear regression, the relationship is specified to have only one predictor variable and the relationship is described by a straight line.