Discovering a relationship of some sort between various data can often be a powerful model to understand the links between different processes. We generally consider the variable Y to be an outcome or dependent on an independent or input variable X. A statistician would speak of the regression of Y on X while a mathematician would write that Y is a function of X. In this chapter and the next, we are going to take our time to properly explore both the underlying logic and the practice of employing linear regression. Our goal is to avoid what is occasionally called "mathyness" and focus on several practical, applied examples that still allow for the correct sorts of ideas to be living in your head.