ABSTRACT
Often it is the case when more than one predictor, or x-variable, has an impact on a given response, or y-variable. For example, suppose we are interested in developing a model that can be used to predict executive salaries. An executive’s salary is determined not only by his or her level of education and the number of years of experience, but also by other factors, such as whether the business is profit or nonprofit, and the number of employees the executive manages. Furthermore, you can probably even think of more factors that could also be used in determining an executive’s salary besides those just mentioned. For instance, the gender of the executive and the region of the country where he or she is employed could also be factors that impact salaries. In order to account for multiple factors having an impact on some outcome or response variable of interest, multiple regression analysis can be used.
