At this point in our Linear Modeling in R course, you've learned how to approach each stage of the modeling process, including how to correctly fit a model and how to assess its accuracy.
But in real-world data science work, you may want to build and test many models at once. Building each model individually would be cumbersome,
Thankfully, there's a package that can help with that! In this mission, you'll learn to use Broom to fit a number of linear models quickly so that you can focus on what's most important: assessing accuracy to pick the best model for your data.
Of course, as you work with the model, you'll also be reviewing programming and statistics concepts from earlier in our Data Analyst in R path.
2. Tidy model outputs with broom::tidy()
3. Introducing the datasets
4. Nested data
5. Generate many linear models
6. Returning tidy model outputs
7. Unnesting to return tidy data summaries
8. Tidy summary statistics with broom::glance()
9. Augment dataframes with broom::augment()