Question

Use the following information to answer the questions below: Heat Power is a utility company that would like to predict the monthly heating bill for a household in a particular region during the month of January. A random sample of 18 households in the region were selected and their January heating bill recorded. The data is shown in the table below along with the square footage of the house (SF), the age of the heating system in years (Age), and the type of heating system (Type: heat pump = 1 or natural gas = 0). Household 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Bill $255 $286 $296 $300 $305 $317 $321 $321 $339 $349 $369 $374 $381 $413 $419 $441 $522 $560 SF 2.070 1,909 2.004 2.307 3,021 2.683 1.511 2.836 2.553 2.497 2.103 2.486 2.279 2.477 3.218 3.080 2.507 3.517 Age 7 17 8 22 5 14 8 3 20 11 12 18 19 17 11 8 20 18 Type Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Heat Pump Heat Pump Heat Pump Heat Pump Heat Pump Heat Pump Heat Pump Heat Pump SUMMARY OUTPUT Regression Statistics Multiple R 0.8655 R Square Adjusted R Square Standard Error 44.8082 Observations 18 ANOVA df MS F Significance F Regression Residual Total 3 14 17 SS 83,948.96 28.108.82 112.057.78 Coefficients Standard Error 144.7200 65.1807 0.0583 0.0237 2.4158 2.0074 95.0806 24.7518 t Stat 2.2203 2.4648 P-value 0.0434 0.0273 Lower 95% Upper 95% 4.921 284.519 0.008 0.109 Intercept SF Age Type 3.8414 0.0018 41.993 148.168

Answer 1

44)

Both stepwise and best subsets methods check assumptions and conditions.

45)

O A point with zero leverage has no effect on the regression slope.

46)

O Variance Inflation Factors.

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