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:

Assessed

Value Selling Price

Observation (000) (000)

1 78.17 94.10

2 80.24 101.90

3 74.03 88.65

4 86.31 115.50

5 75.22 87.50

6 65.54 72.00

7 72.43 91.50

8 85.61 113.90

9 60.80 69.34

10 81.88 96.90

11 79.11 96.00

12 59.93 61.90

13 75.27 93.00

14 85.88 109.50

15 76.64 93.75

16 84.36 106.70

17 72.94 81.50

18 76.50 94.50

19 66.28 69.00

20 79.74 96.90

21 72.78 86.50

22 77.90 97.90

23 74.31 83.00

24 79.85 97.30

25 84.78 100.80

26 81.61 97.90

27 74.92 90.50

28 79.98 97.00

29 77.96 92.00

30 79.07 95.90

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

How good is the model? Explain.

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

Interpret the meaning of the slope.

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