Logistic & Probit Regression in ExcelA model that describes the relationship between a categorical response variable and one or more explanatory variables using a logit or probit function.

Generalized linear models
A generalized linear model (GLM) is a generalization of the linear models by allowing the linear model to be related to the response variable via a link function and an error distribution other than a normal distribution. The unknown model parameters are estimated using maximum-likelihood estimation.
Parameter estimates
Parameter estimates (also called coefficients) are associated with a one-unit change of the predictor, all other predictors being held constant.
Odds ratio estimates
Odds ratios are the increase or decrease in odds associated with a change of the predictor, all other predictors been held constant.
Effect of model hypothesis test
A likelihood ratio or Wald X² test formally tests the hypothesis of whether the model fits the data better than no model.
Effect of term hypothesis test
A likelihood ratio or Wald X² test formally tests the hypothesis of whether a term contributes to the model.