CSCP Practice Exam 2025 – Complete Guide for Exam Prep

Multiple regression involves the use of multiple predictive variables to explain the relationship between these variables and a dependent variable. This statistical method allows for more complex modeling of relationships by considering how multiple factors interact and contribute to a particular outcome.

In multiple regression, each predictive variable can have its own unique impact on the dependent variable, and the model helps in quantifying how changes in the predictor variables are associated with changes in the outcome variable. This approach is particularly useful in fields such as economics, social sciences, and supply chain management, where the behavior of a dependent variable is often influenced by several different factors.

The ability to include multiple predictors enhances the analysis, allowing for better predictions and insights compared to simpler models that might only account for a single variable. This is why option B accurately reflects the essence of multiple regression.