Question

In: Statistics and Probability

You are studying the market value of home in Houston. You collect data from the recent...

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.


  1. State the multiple regression equation.


  1. Interpret the meaning of the slopes, b1 and b2 , in this problem?

  1. Explain why the regression coefficient, b0, has no practical meaning in the context of this problem.

  1. Predict the mean fair market value for a house that has a land area of 0.25 acre and is 55 years old?

  1. 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


Solutions

Expert Solution

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)

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