# Module 4

Multinomial Logistic Regression & Data Management 101

Learning Objectives: Prepare and manage datasets for analysis by applying principles of tidy data and data merging; understand when to use multinomial logistic regression for outcomes with more than two categories; specify the model and reference category; interpret model coefficients and predicted probabilities; apply multinomial logistic regression to real-world categorical data