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 |
21980 | 2357 |
17392 | 2471 |
18216 | 1895 |
15691 | 1117 |
43957 | 5728 |
33624 | 2536 |
15136 | 2188 |
16699 | 1926 |
18218 | 2135 |
16036 | 1409 |
15145 | 1450 |
36050 | 3099 |
31048 | 2742 |
42030 | 3353 |
14435 | 1649 |
38946 | 4001 |
25309 | 3916 |
22934 | 2438 |
16152 | 3585 |
29200 | 2804 |
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.)
TaxesˆTaxes^ = + 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
1,600-square-foot home. (Round coefficient estimates to at
least 4 decimal places and final answer to 2 decimal
places.)
TaxesˆTaxes^
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