Other linear model considerations

Before moving on, there are two additional linear model topics that we need to discuss. The first is the inclusion of a qualitative feature, and the second is an interaction term; both are explained in the following sections.

Qualitative feature

A qualitative feature, also referred to as a factor, can take on two or more levels such as Male/Female or Bad/Neutral/Good. If we have a feature with two levels, say gender, then we can create what is known as an indicator or dummy feature, arbitrarily assigning one level as 0 and the other as 1. If we create a model with just the indicator, our linear model would still follow the same formulation as before, that is, Y = B0 + B1x + e. If we code the feature as male is equal to zero and female is equal to one, then the expectation for male would just be the intercept, B0, while for female it would be B0 + B1x. In the situation where you have more than two levels of the feature, you can create n-1 indicators; so, for...