Statistics: Testing Hypothesis – #50


Question: We want to develop a model to predict the selling price of a home based upon the assessed value. A sample of 30 recently sold single-family houses is selected. The results are as follows:

Observation Value (000) Selling Price (000)
1 78.17 94.1
2 80.24 101.9
3 74.03 88.65
4 86.31 115.5
5 75.22 87.5
6 65.54 72
7 72.43 91.5
8 85.61 113.9
9 60.8 69.34
10 81.88 96.9
11 79.11 96
12 59.93 61.9
13 75.27 93
14 85.88 109.5
15 76.64 93.75
16 84.36 106.7
17 72.94 81.5
18 76.5 94.5
19 66.28 69
20 79.74 96.9
21 72.78 86.5
22 77.9 97.9
23 74.31 83
24 79.85 97.3
25 84.78 100.8
26 81.61 97.9
27 74.92 90.5
28 79.98 97
29 77.96 92
30 79.07 95.9

Develop a regression equation to forecast the selling price of a house given the assessed value.

a. How good is the model? Explain.

b. What does the y-intercept mean? Is that reasonable?

c. Interpret the meaning of the slope.

d. Forecast the selling price of a house with an assessed value of $65,000 and a house with an assessed value of $103,000. What concerns with accuracy do you have over these predictions

only-members
 

log in

reset password

Back to
log in