Data often comprise two or more features (height, diameter, growth rate, and life-span of a plant; age, height, and weight of a baby; math grade and GPA of a student) that are related (taller plants tend to be thicker; older babies tend to be taller and heavier; higher math grades tend to indicate higher GPAs). In this chapter and Chaps. 5 and 6 , we describe these relationships through equations for the underlying random variables. We call these equations statistical models. This chapter introduces linear regression, a modeling framework based on linear functions that have one or multiple inputs and a continuous output. Linear regression is one of the simplest frameworks—yet surprisingly flexible and versatile.