Exercise 6. Assume that we have fitted the data to a simple linear model and arrived at the linear relationship below: \hat{Y}_{i}=9.57+0.78 \times X_{i} Y denotes the house price in

thousands of euro and X its size in square meters. All houses are in a specific area. a). One house in the sample has size equal to 87 square meters. What is the predicted price? b). Assume that for a 87 square meters house, the price is 77. What is the residual? c). Assume that you are interested in selling a 100 square meters house in this area.What price would you sell it? Should we use our model above to make the prediction?Why? d). Assume that we have calculated the Durbin-Watson statistic, which is 2.88. Does the model suffer from auto correlation? If yes, describe a method for correcting it. What problems does autocorrelation cause?