Exercise

# Interaction terms

In the video you learned how to include interactions in the model structure when there is one continuous and one categorical variable. In this exercise you will analyze the effects of interaction between two continuous variables.

You will use centered variables instead of original values to be able to interpret the coefficient effects more easily, i.e. from the level of the mean values rather than 0 which may not be logical for the study at hand. In other words we don't want to interpret the model by assuming 0 for `arsenic`

or `distance100`

variables.

The model `'switch ~ distance100 + arsenic'`

has been preloaded as `model_dist_ars`

in the workspace.

Also `wells`

dataset is preloaded.

Instructions 1/2

**undefined XP**

- Fit a logistic model with
`switch`

as the response and centered`distance100`

,`arsenic`

and the interaction term between`distance100`

and`arsenic`

as explanatory variables. Use`center()`

to center the variables. - Print the model summary.