The adjusted R-square plot is also helpful in selecting a model. Each row of the following plot represents a separate model, with the intercept and all of the variables as columns. The `plot` function shows how adjusted R-square (*y*-axis) changes for each of the variables in the model:

plot(out, scale = "adjr2")

To select an optimal model, look to the point at which variables have black boxes near the top of the *y*-axis range.

For our example, that would mean using the four-variable model **Ozone**, **Month**, **Solar.R**, and **Day**. However, as noted previously, the difference between the two and four variable model seems minimal. ...