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Exercise

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() (docs), broom::glance() (docs), and sigr::wrapFTest() (docs).

The broom and sigr packages have been pre-loaded, and unemployment_model is available for you.

Instructions

100 XP
  • 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.