(a) Assuming that a simple linear regression model is appropriate, obtain the least squares fit relating selling price to taxes paid. What is the estimate of o²? (b) Find the mean selling price given that the taxes paid are x = 7.50. (c) Calculate the fitted value of y corresponding to x = 5.8980. Find the corresponding residual.

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(a) Assuming that a simple linear regression model is appropriate, obtain the least squares fit relating selling price to taxes paid. What is the estimate of o²?

(b) Find the mean selling price given that the taxes paid are x = 7.50.

(c) Calculate the fitted value of y corresponding to x = 5.8980. Find the corresponding residual.

11-4. An article in Technometrics by S. C. Narula and J. F.
Wellington [“Prediction, Linear Regression, and a Minimum
Sum of Relative Errors" (Vol. 19, 1977)] presents data on the
selling price and annual taxes for 24 houses. The data are
shown in the following table.
Тахes
Таxes
(Local, School),
Price/1000 County)/1000
Sale
Sale
(Local, School),
Price/1000 County)/1000
25.9
4.9176
30.0
5.0500
29.5
5.0208
36.9
8.2464
27.9
4.5429
41.9
6.6969
25.9
4.5573
40.5
7.7841
29.9
5.0597
43.9
9.0384
29.9
3.8910
37.5
5.9894
30.9
5.8980
37.9
7.5422
28.9
5.6039
44.5
8.7951
35.9
5.8282
37.9
6.0831
31.5
5.3003
38.9
8.3607
31.0
6.2712
36.9
8.1400
30.9
5.9592
45.8
9.1416
Transcribed Image Text:11-4. An article in Technometrics by S. C. Narula and J. F. Wellington [“Prediction, Linear Regression, and a Minimum Sum of Relative Errors" (Vol. 19, 1977)] presents data on the selling price and annual taxes for 24 houses. The data are shown in the following table. Тахes Таxes (Local, School), Price/1000 County)/1000 Sale Sale (Local, School), Price/1000 County)/1000 25.9 4.9176 30.0 5.0500 29.5 5.0208 36.9 8.2464 27.9 4.5429 41.9 6.6969 25.9 4.5573 40.5 7.7841 29.9 5.0597 43.9 9.0384 29.9 3.8910 37.5 5.9894 30.9 5.8980 37.9 7.5422 28.9 5.6039 44.5 8.7951 35.9 5.8282 37.9 6.0831 31.5 5.3003 38.9 8.3607 31.0 6.2712 36.9 8.1400 30.9 5.9592 45.8 9.1416
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