In regression analyses, what is a predictor variable?

In regression analyses, what is a predictor variable?

• A. The outcome variable.
• B. The residual.
• C. The coefficient.
• D. A variable that is used to predict values of the outcome variable.

Answer: (D)

In regression, a predictor variable is the variable used to predict values of the outcome variable. It serves as the input that helps explain or estimate what you’re trying to forecast. The outcome (or dependent) variable is what you’re predicting, so it’s not the predictor itself. The residual represents the part of the outcome that the model doesn’t explain—the difference between observed and predicted values. The coefficient is the estimated effect size that tells you how much the outcome changes with a one-unit change in the predictor, not the predictor itself. Predictor variables can be continuous or encoded categories (dummy variables) and are the inputs that drive the prediction.

In regression, a predictor variable is the variable used to predict values of the outcome variable. It serves as the input that helps explain or estimate what you’re trying to forecast. The outcome (or dependent) variable is what you’re predicting, so it’s not the predictor itself. The residual represents the part of the outcome that the model doesn’t explain—the difference between observed and predicted values. The coefficient is the estimated effect size that tells you how much the outcome changes with a one-unit change in the predictor, not the predictor itself. Predictor variables can be continuous or encoded categories (dummy variables) and are the inputs that drive the prediction.