One of the coolest things about linear regression is that we are not limited to using predictor variables that are continuous. For example, in the last section, we used the continuous variable `wt` (weight) to predict miles per gallon. But linear models are adaptable to using categorical variables, such as `am` (automatic or manual transmission) as well.

Normally, in a simple linear regression equation, *ŷ = b _{0} + b_{1}x *,

*x*will hold the actual value of the predictor variable. In the case of a simple linear regression with a binary predictor (such as

`am`),

*x*will hold a

*dummy variable*instead. Specifically, when the predictor is automatic,

*x*will be 0, and when the predictor is manual,

*x*will be ...