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3. Exercise 4.3 The county assessor is studying housing demand and is interested in developing a regression model to estimate the market value (i.e., selling

3. Exercise 4.3

The county assessor is studying housing demand and is interested in developing a regression model to estimate the market value (i.e., selling price) of residential property within her jurisdiction. The assessor suspects that the most important variable affecting selling price (measured in thousands of dollars) is the size of house (measured in hundreds of square feet). She randomly selects 15 houses and measures both the selling price and size, as shown in the following table.

Complete the table and then use it to determine the estimated regression line.

Observation Size Selling Price
(x 100 sq. ft.) (x $1,000)

ii

xixi

yiyi

xixiyiyi

xi2xi2

yi2yi2

1 12 265.2 3,182.40 144.00 70,331.04
2 20.2 279.6 5,647.92 408.04 78,176.16
3 27 311.2 8,402.40 729.00 96,845.44
4 30 328.0 9,840.00 900.00 107,584.00
5 30 352.0 10,560.00 900.00 123,904.00
6 21.4 281.2 6,017.68 457.96 79,073.44
7 21.6 292.4 6,315.84 466.56 85,497.76
8 25.2 292.8 7,378.56 635.04 85,731.84
9 37.2 360.0 13,392.00 1,383.84 129,600.00
10 14.4 263.2 3,790.08 207.36 69,274.24
11 15 272.4 4,086.00 225.00 74,201.76
12 22.4 291.2 6,522.88 501.76 84,797.44
13 23.9 299.6 7,160.44 571.21 89,760.16
14 26.6 307.6 8,182.16 707.56 94,617.76
15 30.7 320.4 9,836.28 942.49 102,656.16
Total 357.60 4,516.80 9,179.82

Regression Parameters Estimations
Slope ()
Intercept ()

In words, for each hundred square feet, the expected selling price of a house by $ .

What is the standard error of the estimate (sese)?

10.202

11.289

10.906

What is the estimate of the standard deviation of the estimated slope (sbsb)?

0.426

0.399

0.441

Can the assessor reject the hypothesis (at the 0.05 level of significance) that there is no relationship (i.e., =0=0) between the price and size variables? (Hint: t0.025,13=2.160t0.025,13=2.160)

No

Yes

Complete the following worksheet and then use it to calculate the coefficient of determination.

ii xixi yiyi yy^ (yiy)2y^iy2 (yiy)2yiy^2 (yiy)2yiy2
1 12 265.2 253.4 2,277.2 139.2 1,290.2
2 20.2 279.6 286.4 216.7 46.2 463.1
3 27 311.2 313.7 158.3 6.3 101.6
4 30 328.0 325.8 609.1 4.8 722.5
5 30 352.0 325.8 609.1 686.4 2,588.8
6 21.4 281.2 291.2 98.4 100.0 396.8
7 21.6 292.4 292.0 83.2 0.2 76.0
8 25.2 292.8 306.5 28.9 187.7 69.2
9 37.2 360.0 354.7 2,870.8 28.1 3,466.9
10 14.4 263.2 263.1 1,445.5 0.0 1,437.9
11 15 272.4 265.5 1,268.8 47.6 824.8
12 22.4 291.2 295.2 35.0 16.0 98.4
13 23.9 299.6 301.3 0.0 2.9 2.3
14 26.6 307.6 312.1 120.6 20.3 42.0
15 30.7 320.4 328.6 755.2 67.2 371.7
Total

The coefficient of determination (r2r2) is

The F-ratio is , which means that the assessor reject, at the 5% level of significance, the null hypothesis that there is no relationship between the selling price and the area of the house. (Hint: The critical value of F0.05,1,13F0.05,1,13is 4.67.)

Which of the following is an approximate 95% prediction interval for the selling price of a house having an area (size) of 15 (hundred) square feet?

245.1 to 285.9

173.5 to 217.1

174.9 to 215.7

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