A new model of home selling price has been developed by a realty company. One way to assess if the coefficient estimates have been properly recorded is to construct a simple regression model of the observed selling prices versus the new model predicted prices and check how close the model prices and observed prices are.
a) Let E(sellingprice) = β₀ + β₁ model price. Close to what value should the estimate of β₁ be to determine that there is no error in the recording of the model coefficients?
b) If sellingprice = −0.05 + 0.98 ∗ model price, interpret the meaning of the slope.
c) The 95% confidence interval for the slope was (0.93,1.03). How do you think the new model performed based on this confidence interval.
d) If a house sold at $250 000, what is the predicted selling price of the new model?