Which statement correctly describes the typical nature of the dependent variable in logistic regression?

• A. It is typically binary
• B. It is continuous
• C. It is multiclass
• D. It is ordinal

Answer: (A)

Logistic regression models the probability of a binary outcome. The dependent variable is typically coded as 0 or 1, representing two classes (for example, failure vs. success, absence vs. presence). The model uses the log-odds of the event as a linear function of the predictors and then applies the logistic (sigmoid) function to map those odds to a probability between 0 and 1. This framework is what makes the usual dependent variable in logistic regression binary. If the outcome were continuous, linear regression would be more appropriate; for more than two classes, you’d use multinomial or one-vs-rest approaches; for ordinal outcomes, ordinal logistic regression or related methods are used.