To do this, we typically store the linear model in an intermediate R object and then access the model using other functions. Specifically: Create an intermediate object (I call it “model.1” below) to ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

This shows how well our model predicts or forecasts the future sales, suggesting that the explanatory variables in the model predicted 68.7% of the variation in the dependent variable.