In this exercise, we will predict the number of applications received using the other variables in the College data set. (a) Split the data set into a training set and a test set. (b) Fit a linear model using least squares on the training set, and report the test error obtained. (c) Fit a ridge regression model on the training set, with chosen by cross-validation. Report the test error obtained. (d) Fit a lasso model on the training set, with chosen by crossvalidation. Report the test error obtained, along with the number of non-zero coefficient estimates. (e) Fit a PCR model on the training set, with M chosen by crossvalidation. Report the test error obtained, along with the value of M selected by cross-validation. (f) Fit a PLS model on the training set, with M chosen by crossvalidation. Report the test error obtained, along with the value of M selected by cross-validation.