What characterizes a multiple regression model?

• A. A model with one independent variable
• B. A model with two or more independent variables
• C. A model analyzing a single factor
• D. A model focused on historical data

Answer: (B)

A multiple regression model is characterized by the inclusion of two or more independent variables that are used to explain the variation in a dependent variable. This framework allows researchers and analysts to assess the impact of several factors simultaneously, providing a more comprehensive understanding of relationships within the data.

In contrast, models with only one independent variable are described as simple regression models. A model analyzing a single factor refers to a univariate analysis, which does not capture the complexities that can arise from multiple influences on the dependent variable. Although analyzing historical data can be part of a multiple regression model, it is not a defining characteristic; instead, the focus is on utilizing multiple predictors to explain the outcome. Therefore, the defining trait of a multiple regression model is the utilization of two or more independent variables.