The datasets used in this assignment are contained in the ISLR package in R. You should fit the required models, test the statistical significance of the coefficients, use appropriate model selection techniques and shrinkage as well as anything else that you deem appropriate. You should fit an initial model and then see if you can find a better" model according to whatever criteria you believe to be appropriate. Please specify the final model that you recommend (using only the variables mentioned in the question), and comment on the accuracy of the final model. Using the data in "Auto", fit a multiple linear regression model with "acceleration" as the response and "mpg", "horsepower and weight as the predictors. Comment fully on your results and the proposed model. Your answer is limited to 750 words and you may include graphs if you wish. (please with explanation specifically with shrinkage (ridge or lasso)) The datasets used in this assignment are contained in the ISLR package in R. You should fit the required models, test the statistical significance of the coefficients, use appropriate model selection techniques and shrinkage as well as anything else that you deem appropriate. You should fit an initial model and then see if you can find a better" model according to whatever criteria you believe to be appropriate. Please specify the final model that you recommend (using only the variables mentioned in the question), and comment on the accuracy of the final model. Using the data in "Auto", fit a multiple linear regression model with "acceleration" as the response and "mpg", "horsepower and weight as the predictors. Comment fully on your results and the proposed model. Your answer is limited to 750 words and you may include graphs if you wish. (please with explanation specifically with shrinkage (ridge or lasso))