Question
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
Step by Step Solution
There are 3 Steps involved in it
Step: 1
Get Instant Access to Expert-Tailored Solutions
See step-by-step solutions with expert insights and AI powered tools for academic success
Step: 2
Step: 3
Ace Your Homework with AI
Get the answers you need in no time with our AI-driven, step-by-step assistance
Get Started