predicting boston housing prices: the file bostonhousing.xls contains information collected by the us bureau of the census concerning houses in the area of boston. the dataset includes 506 houses. the goal is to predict the median house price in a new tracts based on information such as crime rate, pollution, and number of rooms. the dataset contains 12 predictors, and the response is the median house price (medv). a. why should the data be partitioned into training and validation sets? what will the training set be used for? what will the validation set be used for? b. fit a multiple linear regression model to the median house price (medv) as a function of crim, chas, and rm. write the equation for prediction. c. using the estimated regression model, what median house price is predicted for a tract in the boston area that does not bound the charles river, has a crime rate of 0.1, and where the average number of rooms per house is 6