The document outlines a procedure for utilizing the mpg.csv dataset to perform a basic linear regression analysis. It involves identifying key variables from the training set, calculating various accuracy metrics, and subsequently evaluating the model's performance on a test set with similar measures. The focus is on ensuring a thorough understanding of model accuracy and variable importance.

1. Using the Mpg.csv dataset
(b) Run a basic linear regression and identify the important variables against the training set.
(c) Once you have a model, provide measures of accuracy (e.g. ME, MAE, MPE, MAPE, RMSE,
etc) for the training set
(d) Run the model against the test set and provide measures of accuracy.