We will start with a model that includes all variables available to explain mpg. Then we perform stepwise model selection in order to select significant predictors for the final, best model. The step function will perform this selection by calling lm repeatedly to build multiple regression models and select the best variables from them using both forward selection and backward elimination methods using AIC algorithm. This ensures that we have included useful variables while omitting ones that do not contribute significantly to predicting mpg.