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Binary, Ordinal, and Multinomial Logistic Regression for Categorical Outcomes

with Karen Grace-Martin
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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.

Covered in this webinar:

  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
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