Use the software instructions provided to develop a model using best subsets techniques. Stepwise regression simply states which model to use, while best subsets provides much more information and requires the user to choose how many variables to include in the model. In general, statisticians select models that have a relatively low C_p, a large R², and a relatively small number of explanatory variables. (It is rare for these statistics to all suggest the same model. Thus, the researcher much choose a model based on his or her goals. The extended activities provide additional details about each of these statistics.) Based on the output from best subsets, which explanatory variables should be included in a regression model?