Binary logistic regression examines the relationship between one or more predictor variables and a binary response. A binary response variable has two possible outcomes, such as the presence or absence of a disease.

Factors and covariates can be used as predictors in a binary logistic model. The fitted binary logistic model is sometimes used to classify observations into one of two categories.

A cereal company is investigating the effectiveness of a TV advertisement for a new product called Cocoa Crunch. After showing the advertisement in a particular community for one week, they randomly sampled seventy-one adults exiting a local supermarket.

They were asked:

·    whether or not they bought Cocoa Crunch (Bought)

·    their household income (in thousands of dollars) (Income)

·    whether or not they had children (Children)

·    whether or not they viewed the advertisement (ViewAd)

Data: CerealAd.MTW (available in the Sample Data folder).