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 a fraud or legitimate, sales quote sent to a customer being successful or not, job applications succeed 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 section ...
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