# 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