Exercise

# Including an interaction

Just as in the case with one numeric and one categorical explanatory variable, it is possible that numeric explanatory variables can interact. With this model structure, you'll get a third slope coefficient: one for each explanatory variable and one for the interaction.

Here you'll run and predict the same model as in the previous exercise, but this time including an interaction between the explanatory variables.

`taiwan_real_estate`

is available; `dplyr`

, `tidyr`

and `ggplot2`

are loaded.

Instructions 1/3

**undefined XP**

- Fit a linear regression of house price versus the number of convenience stores and the square-root of the distance to the nearest MRT stations,
*with*an interaction, using the`taiwan_real_estate`

dataset.