The accompanying table shows a portion of a data set that refers to the property taxes owed by a homeowner (in $) and the size of the home (in square feet) in an affluent suburb 30 miles outside New York City.
Taxes | Size |
21,987 | 2,352 |
17,343 | 2,362 |
⋮ | ⋮ |
29,272 | 2,878 |
Taxes | Size | |
21987 | 2352 | |
17343 | 2362 | |
18279 | 1776 | |
15645 | 1118 | |
43954 | 5712 | |
33653 | 2592 | |
15105 | 2134 | |
16749 | 1905 | |
18239 | 2024 | |
16048 | 1389 | |
15135 | 1381 | |
36016 | 3028 | |
31083 | 2771 | |
42000 | 3374 | |
14370 | 1556 | |
38953 | 3971 | |
25373 | 3934 | |
22971 | 2321 | |
16169 | 3557 | |
29272 | 2878 | |
a. Estimate the sample regression equation that enables us to predict property taxes on the basis of the size of the home. (Round your answers to 2 decimal places.)
taxes= ____ + ____size
b. Interpret the slope coefficient.
As Size increases by 1 square foot, the property taxes are predicted to increase by $6.91.
As Property Taxes increase by 1 dollar, the size of the house increases by 6.91 ft.
c. Predict the property taxes for a
1,200-square-foot home. (Round coefficient estimates to at
least 4 decimal places and final answer to 2 decimal
places.)
Taxes=
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