What is the purpose of multiple regression analysis?

Multiple regression analysis is used primarily to predict the value of a dependent variable based on the values of multiple independent variables. This statistical technique allows researchers to assess the relationships between several predictors and the outcome, enabling more comprehensive models that reflect the complexity of real-world influences on the dependent variable. By including multiple independent variables, regression can show how they collectively impact or explain the variance in the dependent variable, and it also helps in understanding the individual contributions of each predictor while controlling for the effects of the other variables in the model. This ability to make predictions is one of the primary reasons for employing multiple regression in research and program evaluation.