**Factual**

What is the best way to handle NA values when performing a regression?

When will the quantiles graph for a regression model not look like a nice line of fit?

Can you compare the anova versus manova results? Aside from the multiple sections, is there really a difference in the calculations?

**When, how, and why?**

Why does the

**Residuals vs Leverage**graph show such a blob of data?Why do we use 4 as a rounding number in the robust regression?

At what point will you feel comfortable deciding that the dataset you are using for a regression has the right set of predictors in use?

**Challenges**

Are there better predictors available for obesity than those used in the chapter?

How can multilevel regression be used for either the obesity or mpg datasets?

Can you determine a different set of predictors for mpg that does not reduce it to simple government fiat?