Question:
A random sample of data was collected on residential sales in a large city. The following table shows the sales price Y (in $ 1,000s), area X1 (in hundreds of square feet), number of bedrooms X2, total number of rooms X3, age X4 (in years), and location (dummy variables Z1 and Z2, defined as follows: Z1 = Z2 = 0 for intown; Zl = 1, Z2 = 0 for inner suburbs; Z1 = 0, Z2 = 1 for outer suburbs) of each house.
a. Identify a single regression model that uses the data for all three locations and that defines straight-line models relating sales price (Y) to area (X1) for each location.
b. Using the computer output given next, determine and plot the fitted straight lines for each location.
c. Test the null hypothesis that the straight lines for the three locations coincide.
d. Test H0: "The lines are parallel" versus HA: "The lines are not parallel."
e. In light of your answers to parts (c) and (d), comment on differences and similarities in the sales price-area relationship for the three locations.
Transcribed Image Text:
| 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 1100-00 10 2 5 1 8 2 8 2 1 1 5 8 8 8 1 1 5 8 9 2 9 2 6 1 583583 X, , | 3 2 2 3 3 3 3 3 3 3 3 3 3 2 3 3 2 3 3 2 3 2 3 3 3 3 3 3 3 3 00 .1 2 2 2 2 3 3 3 4 4 4 ,5 5 5 6 6 .7 7 .7 .7 .9 9 9009 .9 .9 ^| 84 93 83 85 85 85 85 63 84 84 77 92 9 1 8 8 40 81 86 89 86 89 75 78 87 99 87 90 91 2 3 4 5 6 7 8 9 0 1 2 3 5 6 7 S 9 2 567890 1 2 2 2 2 2 2 2 2 Regression of Sales Price (Y) on Area (X1), Location (Z), and XZ DESCRIPTIVE STATISTICS Standard Deviation Variable Intercopt X1 Z1 Sum Moan Uncorrected SS Variance 1.00000 423.90000 14 13000 7.00000 0.23333 5.00000 0.50000 00.80000 336000 204 20000 6.80667 2504.90000 83.49667 30.00000 30.00000 6276.55000 7.00000 15.00000 1490.94000 3.14502 0.43018 0.50855 6.30340 24959 122.5520611.07032 9.89114 0.18506 0.25862 9.73283 6 X121 X122 2914 06000 5255651 212705 ANALYSIS OF VARIANCE Sum of Source Model Error Corrected Total Mean SquareF 631 68288 38.32 0001 16.48314 DFI Squares F Value Pr>F 5 3158.414416 395.59526 24 29 3554.00967 Root MSE Dependent Mean Coeff Var 4.05994 83.49667 4.86240 R-Square Adj R-Sq 0.8887 0.8655 PARAMETER ESTIMATES Parameter Standard Type I SS VariableF Estimate Intercept X1 Error t Value Pr 209151 4,80699 0.39735 12.10 0002271.71350 0.01631 336.00295 89 28227 8 96861 6.07754 1.48 0.1530 1 52 12239 11.22484 464 00001 48.558247.79710 6.23 0001 1-3 20121075896 422 0.0003 5.29 0001 X121 12 803092981520 001 X122 461.3993