It is now time to apply all that we have seen until now to our data. First of all, we are going to fit our model, applying the previously introduced lm() function. This will not require too much time, and will directly lead us to model assumptions validation, both on multicollinearity and residual behavior. We will finally, for the best possible model, apply both stepwise regression and principal component regression.