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.

This exercise is part of the course

Intermediate Regression in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

mdl_price_vs_conv %>% 
  # Get the model-level coefficients
  ___ %>% 
  # Pull out the RSE
  ___

# Get the RSE for mdl_price_vs_age
mdl_price_vs_age %>% 
  ___


# Get the RSE for mdl_price_vs_both
mdl_price_vs_both %>% 
  ___

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