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pose a scheduled airline flight must average at least 65% occupancy in order to be profitable to the airline. Occupancy rates were recorded daily for a regularly scheduled flight on each of 120 days, showing a mean occupancy per flight of 63% a iation of 10%. If 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. ⒸHO: H= 65 versus H₂: μ> 65 O Ho: μ< 65 versus H₂: μ > 65 Ho: 65 versus H₂: μ = 65 OH: H=65 versus H₂: # < 65 ⒸH₂: H=65 versus H₂: μ = 65 Does the alternative hypothesis in part (a) imply a one- or two-tailed test? Explain. O Since small or large values of x would tend to disprove the null hypothesis, this is a two-tailed test. O Since only large values of x would tend to disprove the null hypothesis, this is a one-tailed test. O Since only small values of x would tend to disprove the null hypothesis, this is a one-tailed test. O Since only large values of x would tend to disprove the null hypothesis, this is a two-tailed test. O Since only small values of x would tend to disprove the null hypothesis, this is a two-tailed test. Do the occupancy data for the 120 flights suggest that this scheduled flight is unprofitable? Test using a = 0.05. (Round your answers to two decimal places. If the test is one-tailed, enter NONE for the unused region.) test statistic rejection region z> z < State your conclusion. O Ho is not rejected. There is sufficient evidence to indicate that the flight is unprofitable. O Ho is rejected. There insufficient evidence to indicate that the flight is unprofitable. O Ho is rejected. There is sufficient evidence to indicate that the flight is unprofitable.

pose a scheduled airline flight must average at least 65% occupancy in order to be profitable to the airline. Occupancy rates were recorded daily for a regularly scheduled flight on each of 120 days, showing a mean occupancy per flight of 63% a iation of 10%. If 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. ⒸHO: H= 65 versus H₂: μ> 65 O Ho: μ< 65 versus H₂: μ > 65 Ho: 65 versus H₂: μ = 65 OH: H=65 versus H₂: # < 65 ⒸH₂: H=65 versus H₂: μ = 65 Does the alternative hypothesis in part (a) imply a one- or two-tailed test? Explain. O Since small or large values of x would tend to disprove the null hypothesis, this is a two-tailed test. O Since only large values of x would tend to disprove the null hypothesis, this is a one-tailed test. O Since only small values of x would tend to disprove the null hypothesis, this is a one-tailed test. O Since only large values of x would tend to disprove the null hypothesis, this is a two-tailed test. O Since only small values of x would tend to disprove the null hypothesis, this is a two-tailed test. Do the occupancy data for the 120 flights suggest that this scheduled flight is unprofitable? Test using a = 0.05. (Round your answers to two decimal places. If the test is one-tailed, enter NONE for the unused region.) test statistic rejection region z> z < State your conclusion. O Ho is not rejected. There is sufficient evidence to indicate that the flight is unprofitable. O Ho is rejected. There insufficient evidence to indicate that the flight is unprofitable. O Ho is rejected. There is sufficient evidence to indicate that the flight is unprofitable.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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**Title: Statistical Hypothesis Testing for Airline Occupancy Rates** Suppose a scheduled airline flight must average at least 65% occupancy in order to be profitable to the airline. Occupancy rates were recorded daily for a regularly scheduled flight on each of 120 days, showing a mean occupancy per flight of 63% and a standard deviation of 10%. **(a)** If \( \mu \) 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. - \( H_0: \mu = 65 \) versus \( H_a: \mu < 65 \) - \( H_0: \mu < 65 \) versus \( H_a: \mu = 65 \) - \( H_0: \mu = 65 \) versus \( H_a: \mu \neq 65 \) - \( H_0: \mu = 65 \) versus \( H_a: \mu > 65 \) - \( H_0: \mu > 65 \) versus \( H_a: \mu = 65 \) **(b)** Does the alternative hypothesis in part (a) imply a one- or two-tailed test? Explain. - Since small or large values of \( \bar{x} \) would tend to disprove the null hypothesis, this is a two-tailed test. - Since only large values of \( \bar{x} \) would tend to disprove the null hypothesis, this is a one-tailed test. - Since only small values of \( \bar{x} \) would tend to disprove the null hypothesis, this is a one-tailed test. - Since only large values of \( \bar{x} \) would tend to disprove the null hypothesis, this is a two-tailed test. - Since only small values of \( \bar{x} \) 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 \( \alpha = 0.05 \). (Round your answers to two decimal places. If the test is one-tailed, enter NONE for the unused region.) - Test Statistic: \( z = \_\_\_\_ \) - Rejection Region: \( z >
Transcribed Image Text:**Title: Statistical Hypothesis Testing for Airline Occupancy Rates** Suppose a scheduled airline flight must average at least 65% occupancy in order to be profitable to the airline. Occupancy rates were recorded daily for a regularly scheduled flight on each of 120 days, showing a mean occupancy per flight of 63% and a standard deviation of 10%. **(a)** If \( \mu \) 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. - \( H_0: \mu = 65 \) versus \( H_a: \mu < 65 \) - \( H_0: \mu < 65 \) versus \( H_a: \mu = 65 \) - \( H_0: \mu = 65 \) versus \( H_a: \mu \neq 65 \) - \( H_0: \mu = 65 \) versus \( H_a: \mu > 65 \) - \( H_0: \mu > 65 \) versus \( H_a: \mu = 65 \) **(b)** Does the alternative hypothesis in part (a) imply a one- or two-tailed test? Explain. - Since small or large values of \( \bar{x} \) would tend to disprove the null hypothesis, this is a two-tailed test. - Since only large values of \( \bar{x} \) would tend to disprove the null hypothesis, this is a one-tailed test. - Since only small values of \( \bar{x} \) would tend to disprove the null hypothesis, this is a one-tailed test. - Since only large values of \( \bar{x} \) would tend to disprove the null hypothesis, this is a two-tailed test. - Since only small values of \( \bar{x} \) 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 \( \alpha = 0.05 \). (Round your answers to two decimal places. If the test is one-tailed, enter NONE for the unused region.) - Test Statistic: \( z = \_\_\_\_ \) - Rejection Region: \( z >
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