Abstract
One of the simplest statistical models that can be used to model the relationship between a continuous response variable and a single quantitative explanatory variable is the simple linear regression model. This chapter discusses the use of simple linear regression for modeling a response variable as a linear function of a single explanatory variable. In particular, bivariate data summary statistics, components of a simple linear regression model, fitting a simple linear regression model, assessing the fit of a simple linear regression model, and the statistical inferences that can be made from a simple linear regression model are discussed. When the data cloud in a scatterplot of the response variable versus the explanatory variable is linear, a plausible model for approximating the relationship between the response and explanatory variable is the simple linear regression model.
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