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We want to develop a model to predict the selling price of a home based upon the assessed value. A s

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

Price: $2.99

Answer: The solution consists of 4 pages
Type of Deliverable: Word Document