Exercise

# With and without an interaction term

In the linear model architecture, you specify an interaction between two explanatory variables by using `*`

notation rather than `+`

.

In this exercise, you'll compare models of birth weight as a function of gestational period and the mother's smoking status. One model will not have an interaction between the two and the other will.

Recall that an interaction describes how one explanatory variable (e.g. `smoke`

) changes the effect size of the other (e.g. `gestation`

).

Instructions

**100 XP**

- Train a linear model with the formula
`baby_wt ~ gestation + smoke`

and the data`Birth_weight`

- Train another linear model similar to the first, but include an interaction between
`gestation`

and`smoke`

. - Use
`fmodel()`

to plot each model and note the difference between the two. Note that, in this case, you don't have to specify any additional arguments to`fmodel()`

beyond the model; it automatically figures out the best way to plot things.