Logistic regression is a method of estimating the probability of an outcome for binary categorical variables. The variable of interest is often an event. The occurrence of this event is considered “success,” and otherwise “failure.” Examples include insurance claims being fraudulent or legitimate, a sale quote sent to a customer being successful or not, job applications succeeding or not, and if age is a factor in tendency to buy a product or service. A simple example of one predictor for the outcome is a binary dependent variable and a continuous predictor. Similar to multiple linear regression, we may have multiple predictors including categorical variables, and a nominal or ordinal response variable. The next ...
Get Introduction to Business Analytics, Second Edition now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
