Reference no: EM132413689

Suppose a scheduled airline flight must average at least 65% occupancy in order to be profitable to the airline. An examination of the occupancy rate for 120 10:00 a.m. flights from Atlanta to Dallas showed a mean occupancy per flight of 63% and a standard deviation of 10%.

(a) If μ is the mean occupancy per flight and if the company wishes to determine whether or not this scheduled flight is unprofitable, give the alternative and the null hypotheses for the test.

H₀: μ = 65 versus H_a: μ ≠ 65

H₀: μ = 65 versus H_a: μ < 65    

H₀: μ ≠ 65 versus H_a: μ = 65

H₀: μ < 65 versus H_a: μ > 65

H₀: μ = 65 versus H_a: μ > 65

(b) Does the alternative hypothesis in part (a) imply a one- or two-tailed test? Explain.

Since only small values of x would tend to disprove the null hypothesis, this is a one-tailed test.

Since only large values of x would tend to disprove the null hypothesis, this is a one-tailed test.    

Since only large values of x would tend to disprove the null hypothesis, this is a two-tailed test.

Since only small values of x would tend to disprove the null hypothesis, this is a two-tailed test.

Since small or large values of x would tend to disprove the null hypothesis, this is a two-tailed test.

(c) Do the occupancy data for the 120 flights suggest that this scheduled flight is unprofitable? Test using α = 0.05. (Round your answers to two decimal places. If the test is one-tailed, enter NONE for the unused region.)

test statisticz=rejection regionz>z<

State your conclusion.

H₀ is rejected. There is insufficient evidence to indicate that the flight is unprofitable.

H₀ is not rejected. There is sufficient evidence to indicate that the flight is unprofitable.    

H₀ is not rejected. There is insufficient evidence to indicate that the flight is unprofitable.

H₀ is rejected. There is sufficient evidence to indicate that the flight is unprofitable.