Which outcome is typically produced by logistic regression?

• A. A Binary Outcome
• B. A Regression Line
• C. A Cluster Assignment
• D. A Covariance Matrix

Answer: (A)

Logistic regression is used to model the probability of a binary outcome. It takes input features, forms a linear combination, and passes it through the logistic function, which constrains the result to a value between 0 and 1. That value is interpreted as the probability of the positive class, and it can be thresholded (often at 0.5) to produce a binary decision.

This is why the typical outcome is a binary one: the model is built to distinguish between two classes. It doesn’t directly output a regression line like linear regression, since the relationship is captured in the log-odds via the logistic function. It isn’t a clustering method, which would assign items to groups, nor does it produce a covariance matrix, which summarizes relationships among variables.