Examining a model

Let's look at the model unemployment_model that you have just created. There are a variety of different ways to examine a model; each way provides different information. We will use summary(), broom::glance(), and sigr::wrapFTest().

The object unemployment_model is in your workspace.

Print unemployment_model again. What information does it report?
Call summary() on unemployment_model. In addition to the coefficient values, you get standard errors on the coefficient estimates, and some goodness-of-fit metrics like R-squared.
Call glance() on the model to see the performance metrics in an orderly data frame. Can you match the information from summary() to the columns of glance()?
Now call wrapFTest() on the model to see the R-squared again.

Exercise

Examining a model

Instructions