What is multiple regression used for?

Multiple regression is a powerful statistical technique primarily utilized for making predictions about a single dependent variable utilizing two or more independent variables. This method allows researchers and analysts to understand the relationship between these variables and how they impact the outcome of interest.

In practical terms, when you have a complex scenario where multiple factors could influence a particular outcome—such as predicting sales based on advertising spend, market conditions, and consumer behavior—multiple regression enables you to input all these independent variables into the model. The technique then quantifies the strength and type of relationship each independent variable has with the dependent variable, leading to a more informed prediction.

Understanding this method is crucial in data-driven decision-making, as it enables organizations to leverage multiple inputs to forecast outcomes effectively, rather than relying on a single factor, which may not provide a complete picture. This is why option B stands out as the correct choice.