Exercise

# Comparing coefficients of determination

Recall that the coefficient of determination is a measure of how well the linear regression line fits the observed values. An important motivation for including several explanatory variables in a linear regression is that you can improve the fit compared to considering only a single explanatory variable.

Here's you'll compare the coefficient of determination for the three Taiwan house price models, to see if which gives the best result.

`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 unadjusted and adjusted coefficients of determination for
`mdl_price_vs_conv`

by glancing at the model, then selecting the`r.squared`

and`adj.r.squared`

values. - Do the same for
`mdl_price_vs_age`

and`mdl_price_vs_both`

.