For binary logistic regression, Minitab shows two types of regression equations. The first equation relates the probability of the event to the transformed response.
The second equation relates the predictors to the transformed response. If the model contains both continuous and categorical predictors, the second equation can be separated for each combination of categories.
Use the equations to examine the relationship between the response and the predictor variables.
For example, a model to predict whether a customer buys a product has these terms:
- Customer's income
- Whehter the customer viewed the ad
The first equation shows the relationship between the probability and the response.
The second set of equations show how income and whether the individual viewed the cereal ad relate to the response. The coefficient for income is about 0.02, whether or not the customer views the ad. For these equations, the more income a customer has, the more likely they are to buy the product.
P(1) = exp(Y')/(1 + exp(Y'))
Y' = −2.4148 + 0.02656 Income
Y' = −1.2946 + 0.02656 Income