This episode is about working with categorical outcomes—questions where results fall into categories rather than a numeric scale.
We learn how to check whether two variables are related, how to model the chance of a “yes/no” outcome using multiple predictors, and how to compare different modeling choices.
We finish with simple ways to judge how well a model fits and whether a simpler or more detailed model is the better choice.
