Exercise

# Adding a linear smoother

You've seen how to add LOESS smoothers to a scatterplot by using both the `add_markers()`

and `add_lines()`

traces. Adding a linear smoother uses the same approach, but you use `lm()`

command to fit the linear model.

In this exercise, your task is to add a linear smoother to a scatterplot of user score against critic score for video games in 2016.

When you add smoothers, missing values (`NA`

s) can be problematic because many modeling functions automatically delete missing observations. To avoid this conflict, use `select()`

and `na.omit()`

to delete observations before plotting.

Note that `plotly`

and the `vgsales2016`

data has already been loaded for you.

Instructions

**100 XP**

- Fit a linear regression model using
`Critic_Score`

as the predictor variable and`User_Score`

as the response variable. Store this model in the object`m`

. - Create a scatterplot showing
`Critic_Score`

on the x-axis and`User_Score`

on the y-axis. - Add a linear smoother to your scatterplot representing the fitted values.