Get beyond the frustration of learning odds ratios, logit link functions, and proportional odds assumptions on your own!

Logistic regression is one of the most useful tools you can have in your statistical tool box.

The different types can be used in a common data situation when linear models can't - when the outcome variable is categorical.

They are a little trickier to learn than linear models, but once you get the idea, you'll see that they're well within your reach.

1.

The three flavors of logistic regression: binary, nominal, and ordinal for three types of categorical outcomes

2.

How to decide which one to use

3.

How to interpret results

4.

How all three types relate to linear regression