In: Statistics and Probability
You are studying the market value of home in Houston. You collect data from the recent sale of 30 single family homes. The data is organized and stored in an Excel file. The dataset includes the fair market value (in $thousands), land area of the property in acres, and age, in years of the 30 homes. Develop a multilinear regression model to predict the fair market value based on land area of the property (in acres) and age, in years.
The name of the Excel data file is HoustonHomes.xlsx. Import the data into SPSS and complete the assignment using SPSS.
State the multiple regression equation.
Interpret the meaning of the slopes, b1 and b2 , in this problem?
Explain why the regression coefficient, b0, has no practical meaning in the context of this problem.
Predict the mean fair market value for a house that has a land area of 0.25 acre and is 55 years old?
Construct a 95% prediction interval estimate for the fair market value for an individual house that has a land area of 0.25 acre and is 55 years old.
Address | Fair Market Value ($000) | Property Size (acres) | Age | House Size (square feet) | Rooms | Baths | Garage |
9 Sycamore Road | 522.9 | 0.2297 | 56 | 2448 | 7 | 3.5 | 2 |
21 Jefferson St | 425.0 | 0.2192 | 61 | 1942 | 7 | 2.5 | 1 |
38 Hitching Post Lane | 539.2 | 0.1630 | 39 | 2073 | 5 | 3 | 2 |
4 Poppy Lane | 628.2 | 0.4608 | 28 | 2707 | 8 | 2.5 | 1 |
5 Daniel Drive | 490.4 | 0.2549 | 56 | 2042 | 7 | 1.5 | 1 |
15 Francis Terrace | 487.7 | 0.2290 | 98 | 2089 | 7 | 2 | 0 |
23 Guilfoy Street | 370.3 | 0.1808 | 58 | 1433 | 7 | 2 | 0 |
17 Carlyle Drive | 777.9 | 0.5015 | 17 | 2991 | 9 | 2.5 | 1 |
8 Craft Avenue | 347.1 | 0.2229 | 62 | 1008 | 5 | 1 | 0 |
22 Beechwood Ct. | 756.8 | 0.1300 | 25 | 3202 | 8 | 2.5 | 2 |
14 Fox Street | 389.0 | 0.1763 | 64 | 2230 | 8 | 2 | 0 |
1 Raynham Road | 889.0 | 1.3100 | 62 | 1848 | 7 | 2 | 1 |
2 Jerome Drive | 452.2 | 0.2520 | 56 | 2100 | 6 | 2 | 0 |
7 Valentine Street | 412.4 | 0.1148 | 22 | 1846 | 5 | 3 | 1 |
38 Jefferson Street | 338.3 | 0.1693 | 74 | 1331 | 5 | 1 | 1 |
15 Inwood Road | 334.3 | 0.1714 | 62 | 1344 | 8 | 1 | 0 |
29 Meadowfield Lane | 437.4 | 0.3849 | 54 | 1822 | 6 | 2 | 1 |
13 Westland Drive | 644.0 | 0.6545 | 56 | 2479 | 6 | 2.5 | 2 |
79 Valentine Street | 387.8 | 0.1722 | 62 | 1605 | 6 | 3 | 0 |
13 Fairmont Place | 399.8 | 0.1435 | 88 | 2080 | 11 | 2 | 0 |
1 Prestwick Terrace | 356.4 | 0.2755 | 81 | 2410 | 6 | 1 | 1 |
11 Clement Street | 346.9 | 0.1148 | 107 | 1753 | 8 | 2 | 0 |
7 Woodland Road | 541.8 | 0.3636 | 55 | 1884 | 7 | 2 | 2 |
36 Elm Avenue | 388.0 | 0.1474 | 51 | 2050 | 10 | 2 | 2 |
17 Duke Place | 564.0 | 0.2281 | 50 | 2978 | 6 | 2.5 | 2 |
12 Prospect Avenue | 454.4 | 0.4626 | 92 | 2132 | 7 | 1 | 0 |
1 Buckeye Road | 417.3 | 0.1889 | 64 | 1551 | 6 | 2 | 0 |
30 Ann Street | 318.8 | 0.1228 | 54 | 1129 | 5 | 1 | 0 |
26 Broadfield Place | 519.8 | 0.1492 | 44 | 1674 | 7 | 2 | 1 |
16 Jackson Street | 310.2 | 0.0852 | 104 | 1184 | 5 | 1 | 0 |
a) Let the multiple linear regression equation be y = b0 + b1x1 +b2x2
b)
Regression Analysis: Fair Market Value ($000) versus ... ize (acres), Age
Analysis of Variance
Source | DF | Adj SS | Adj MS | F-Value | P-Value |
Regression | 2 | 422043 | 211021 | 31.32 | 0.000 |
Property Size (acres) | 1 | 265946 | 265946 | 39.47 | 0.000 |
Age | 1 | 115900 | 115900 | 17.20 | 0.000 |
Error | 27 | 181915 | 6738 | ||
Total | 29 | 603958 |
Model Summary
S | R-sq | R-sq(adj) | R-sq(pred) |
82.0829 | 69.88% | 67.65% | 62.19% |
Coefficients
Term | Coef | SE Coef | T-Value | P-Value | VIF |
Constant | 532.3 | 48.7 | 10.94 | 0.000 | |
Property Size (acres) | 407.1 | 64.8 | 6.28 | 0.000 | 1.01 |
Age | -2.826 | 0.681 | -4.15 | 0.000 | 1.01 |
Regression Equation
Fair Market Value ($000) | = | 532.3 + 407.1 Property Size (acres) - 2.826 Age |
Interpretation of b1 :- The slope coefficient of Property size is 407.1 which says that with increase in 1 acre of property size there will be an increase of 407.1 thousand dollars in Fair market value by keeping the others constant.
Interpretation of b2 :- The slope coefficient of Age is -2.826 which says that with increase in 1 year of age there will be a decrease 2.826 thousand dollars in Fair market value by keeping the others constant.
Interpretation of b0 :- The intercept 532.3 thousand dollars does not have any meaning in this case because if there is no land area and at zero age there wont be any fair market value.
Given a land area of 0.25 acre and is 55 years old
Fair Market Value ($000) = 532.3 + 407.1 Property Size (acres) - 2.826 Age = 532.3 + 407.1*0.25 - 2.826*55 = 478.658
Prediction for Fair Market Value ($000) = 478.658 thousand dollars.
Regression Equation
Fair Market Value ($000) | = | 532.3 + 407.1 Property Size (acres) - 2.826 Age |
Settings
Variable | Setting |
Property Size (acres) | 0.25 |
Age | 55 |
95% Prediction interval
Fit | SE Fit | 95% CI | 95% PI |
478.658 | 15.5086 | (446.837, 510.479) | (307.258, 650.058) |