Exercise

# Comparing residual standard error

The other common metric for assessing model fit is the residual standard error (RSE), which measures the typical size of the residuals.

In the last exercise you saw how including both explanatory variables into the model increased the coefficient of determination. How do you think using both explanatory variables will change the RSE?

`mdl_price_vs_conv`

, `mdl_price_vs_age`

, and `mdl_price_vs_both`

are available; `dplyr`

and `broom`

are loaded.

Instructions 1/2

**undefined XP**

- Get the residual standard error for
`mdl_price_vs_conv`

by glancing at the model, then pulling the`sigma`

value. - Do the same for
`mdl_price_vs_age`

. - Do the same for
`mdl_price_vs_both`

.