Import the data set using pd$.$read$\_$excel and report the shape $($rows$,$ columns$)$ of data.

Remove the variables INSTNM and Appl from the dataset. Split the data set into a training set $(60\%)$ and a validation set $(40\%)$ and use random$\_$state$=5555.$ Keep the variable UNITID but it is just an ID so should NOT be used in any analysis or modeling.

Provide the descriptive statistics of the variable Ug$\_$enter, the total number of entering students at undergraduate level.

If we are to predict the variable Ug$\_$enter using other variables with linear regression, provide at least two appropriate EDAs prior to modeling.

Drop missing values using $.$dropna$()$ function. Report the size of the remaining training and validation data sets.

Fit a linear regression model on the training set to predict Ug$\_$enter. Display the model's coefficients and the Mean Squared Error $($MSE$)$ of the validation set.

Perform $5-$fold CV and show the CV error, i$.$e$.,$ the avergae MSE.

Perform LOOCV and show the CV error.