The following partial MINITAB regression output for the fuel consumption data relates to predicting the city's fuel consumption (in MMcF of natural gas) in a week that has an average hourly temperature of 40°F and a chill index of l0.

a. Report (as shown on the computer output) a point estimate of and a 95 percent confidence interval for the mean fuel consumption for all weeks having an average hourly temperature of 40°F and a chill index of 10.
b. Report (as shown on the computer output) a point prediction of and a 95 percent prediction interval for the fuel consumption in a single week that has an average hourly temperature of 40°F and a chill index of 10.
c. Suppose that next week the city's average hourly temperature will be 40°F and the city's chill index will be 10. Also, suppose the city's natural gas company will use the point prediction Å· = 10.333 and order 10.333 MMcF of natural gas to be shipped to the city by a pipeline transmission system. The city will have to pay a fine to the transmission system if the city's actual gas useage y differs from the order of 10.333 MMCF by more than 10.5 percent-that is. is outside of the range [10.333 ± .105(10.333)1 = [9.248, 11.418). Discuss why the 95 percent prediction interval for y-[9.293, 11.374]-says that y is likely to be inside the allowable range and thus makes the city 95 percent confident that it will avoid paying, a fine.
d. Find 99 percent confidence and prediction intervals for the mean and actual fuel consumption referred to in parts a and b. n = 8 and s = .367078. Optional technical note needed.

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New Obs Fit SE Fit 95% CI 95% PI 1 10.333 0.170 (9.895, 10.771) (9.293, 11.374)