Chapter 3 M3: Thinking About Errors

This module kicks off the part of the course where we start to look critically at the regression models we’ve come to know. Are they doing a good job? How can we tell? And what extensions, variations, and other tricks can we use to make them work better, especially if we’re not meeting the usual conditions?

We’ll start by examining a model’s errors to talk about whether it fits the data well. And, hey, while we’re at it…maybe we don’t have to care only about the errors? Or maybe we don’t have to care equally about all the errors?

Some of these sets of notes come with a “response moment.” You don’t need to write down your answers to these (unless they also show up on the pre-class questions assignment), but it’s good to take a minute or so to think about them – they are designed to help you check your own understanding of what you’ve just seen.