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.
Diese Übung ist Teil des Kurses
Intermediate Regression in R
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
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 %>%
___