Multiple linear regression (MLR), often called multiple regression, is a statistical method that harnesses the power of multiple factors to predict the outcome of a particular variable. The main aim of multiple linear regression analysis is to create a model that explains how the different factors are related to the variable of interest. In other words, multiple linear regression analysis help in determining which factors (independent variables) significantly influence the variable of interest (dependent variable). In fact, multiple regression analysis is an extension of the simple linear regression, but when we have more than one predictor.
Based on the above definition, it is clear that a multiple linear regression model is suitable whenever we want to investigate the effects of various factors/predictors on the dependent variable. The general equation of a multiple linear regression is given by;