The first section of this chapter is devoted to describing the linear regression model. In the linear regression model a dependent variable is explained partly as a linear function of an explanatory variable and partly by an error term. The parameters of the linear function, the beta parameters, are viewed as unknown. If we estimate these parameters using the OLS formula then we have what is called the OLS estimator.