Which statement correctly describes when to use multiple regression?

Which statement correctly describes when to use multiple regression?

• A. When you have only one data point per variable.
• B. When you want to test for non-linear relationships.
• C. When you need to compare means across two groups.
• D. When a single independent variable cannot fully explain the dependent variable.

Answer: (D)

Multiple regression is used when you want to explain a dependent variable using more than one predictor, so you can see each predictor’s effect while accounting for the others. The best statement is that you need multiple regression when a single independent variable cannot fully explain the dependent variable, because adding additional predictors helps capture more of what drives the outcome and allows you to assess the unique contribution of each variable. If you only had one predictor, simple regression would suffice; other scenarios like testing for non-linear relationships or comparing means across groups involve different methods (non-linear terms or transformations for non-linearity, t-tests or ANOVA for group means).

Multiple regression is used when you want to explain a dependent variable using more than one predictor, so you can see each predictor’s effect while accounting for the others. The best statement is that you need multiple regression when a single independent variable cannot fully explain the dependent variable, because adding additional predictors helps capture more of what drives the outcome and allows you to assess the unique contribution of each variable. If you only had one predictor, simple regression would suffice; other scenarios like testing for non-linear relationships or comparing means across groups involve different methods (non-linear terms or transformations for non-linearity, t-tests or ANOVA for group means).