In this lesson, two models for paired data are introduced that are also called simple linear regression models.  In the previous lesson, the estimators we derived required no statistical assumptions or very mild statistical assumptions on the error terms.  In this lesson, we will specify two probability distributions that will not only provide for other methods for estimating the model parameters but will also give the underpinnings for inferential procedures on those parameters and others that are associated with regression.