Real estate valuation. A historical market data set of real estate valuations was collected from Sindian District, New Taipei City, Taiwan, and saved in a file. The data consists of the age (in years) of the property, distance to the nearest MRT (Mass Rapid Transit, Singapore) station (in meters), and the number of convenience stores around. The first five and last five observations of the data used to predict the house price per unit area are shown in the accompanying table. Land Occupancy Age MRT Stores Price Freehold Owner 32 84.87882 10 37.9 Freehold Owner 19.5 306.5947 9 42.2 Freehold Owner 13.3 561.9845 5 47.3 Freehold Owner 13.3 561.9845 5 54.8 Freehold Owner 5 390.5684 5 43.1 f f f f f f Leasehold Tenant 13.7 4082.015 0 15.4 Leasehold Tenant 5.6 90.45606 9 50 Leasehold Tenant 18.8 390.9696 7 40.6 Leasehold Tenant 8.1 104.8101 5 52.5 Leasehold Tenant 6.5 90.45606 9 63.9

a. Find the first fit model, E1y2 = b0 + b1x1 + b2x2 + b3x3, to the data, where y = the house price per unit area.

b. Find the estimate of the standard deviation of e for the model and give a practical interpretation of its value.

c. Conduct a test of the global utility of the model. Use a = .05.

d. Do the data provide sufficient evidence to conclude that the house price per unit area decreases as the distance to the nearest MRT station increases? Report the observed significance level of the test and reach a conclusion using a = .05.

e. Find and interpret a 95% confidence interval for b3.