Which term describes the expected relationship outlined in a regression equation?

The term that best describes the expected relationship outlined in a regression equation is prediction. A regression equation models the relationship between independent and dependent variables, enabling one to make predictions about the dependent variable based on the values of the independent variable(s). The primary purpose of regression analysis is to establish a predictive model that can be used to estimate outcomes, thereby facilitating data-driven decisions in business and research contexts.

While causation refers to a cause-and-effect relationship, correlation emphasizes a statistical association between variables without implying one causes the other. Association typically describes a broader link between variables that might not be adequately quantified. Therefore, prediction accurately captures the essence of what a regression equation aims to achieve: forecasting values based on the inputs provided.