In statistics, logistic regression is a type of regression analysis used for predicting the outcome of a categorical (a variable that can take on a limited number of categories) dependent variable based on one or more predictor variables. The probabilities describing the possible outcome of a single trial are modelled, as a function of explanatory variables, using a logistic function.
Logistic regression measures the relationship between a categorical dependent variable and usually a continuous independent variable (or several), by converting the dependent variable to probability scores.
Read more about Logistic Regression: Background, Introduction, Definition, Coefficients, Formal Mathematical Specification, Bayesian Logistic Regression, Extensions, Model Accuracy
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