Binary Logistic Regression Analysis

Use a binary logistic regression analysis to describe the relationship between a set of predictors and a binary response.

A binary response has two outcomes, such as pass or fail. You can include interaction and polynomial terms, perform stepwise regression, fit different link functions, and validate the model with a test sample or with cross-validation.

For example, marketers at a cereal company investigate the effectiveness of an ad campaign for a new cereal. The marketers can use binary logistic regression to determine whether people who saw the ad are more likely to buy the cereal. To see an example, go to Minitab Help: Example of Fit Binary Logistic Model.

To add output from a binary logistic regression analysis, go to Add and complete a form.

Data considerations

The response variable (Y) should be binary. A binary response has two outcomes, such as pass or fail. The predictors (X) can be continuous or categorical. For more details, go to Minitab Help: Data considerations for Fit Binary Logistic Model.

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