What does the term 'multiple regression' refer to?

The term 'multiple regression' refers to a statistical technique that employs two or more independent variables (predictors) to understand their relationship with a single dependent variable. This method allows researchers to assess how changes in the predictor variables impact the dependent variable, enabling a more comprehensive analysis compared to simple regression, which only considers one predictor.

Multiple regression is widely used in various fields, including economics, biology, and social sciences, to analyze trends, make predictions, and inform decision-making processes. It is particularly beneficial when examining complex phenomena where multiple factors may influence an outcome, as it accounts for the simultaneous effects of various independent variables.

In this context, this method enhances the accuracy and depth of analysis by considering the interplay between multiple factors rather than oversimplifying the relationship to just one predictor. This capability is crucial for drawing more nuanced conclusions from data.