Linear regression is a widely used technique to model the association between a dependent variable and one or more independent variables. In the simplest case, which is what will be explored in this post, there is one independent and dependent variable. The linear regression model in the simple form is \(y = ax + b\), with a slope \(a\) and constant \(b\). Ordinary Least Squares is the most common and straightforward approach to fitting a linear regression model. In the Ordinary Least Squares (OLS) setting, the goal when fitting the linear regression model is to keep the d