What is logistic regression and how does it work?

What is logistic regression and how does it work?

Logistic regression is a statistical method used for binary classification. It predicts the probability of a binary outcome based on one or more predictor variables.

Can you explain the difference between logistic regression and linear regression?

Sure! Linear regression predicts continuous outcomes, while logistic regression predicts probabilities for binary outcomes.

What are some common applications of logistic regression?

Common applications include medical diagnosis, credit scoring, and marketing response prediction.

How do you interpret the coefficients in a logistic regression model?

The coefficients represent the change in the log odds of the outcome for a one-unit increase in the predictor variable.

What assumptions does logistic regression make?

Logistic regression assumes a linear relationship between the log odds of the outcome and the predictor variables, and that the observations are independent.