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Engineering, 09.11.2019 00:31 caggh345

The file bostonhousing. csv contains informationcollected by the us bureau of the census concerning housing in the area ofboston, massachusetts. the dataset includes information on 506 census housing tractsin the boston area. the goal is to predict the median house price in new tracts basedon information such as crime rate, pollution, and number of rooms. the dataset contains 13 predictors, and the response is the median house price (medv). answer the following questions. a. why should the data be partitioned into training and validation sets? for what will the training set be used? for what will the validation set be used? fit a multiple linear regression model to the median house price (medv) as a function of crim, chas and rm. b. write the equation for predicting the median house price from the predictors in the model. c. 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? what is the prediction error?

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