Question

Airline companies recognize that empty seats represent lost revenues that can never be recovered. To avoid losing revenues, the companies often book more passengers than there are available seats. Then, when a flight experiences fewer no-shows than expected, some passengers are 'bumped' from their flights (are denied boarding). Incentives are provided to encourage passengers to give up their reserved seat voluntarily, but occasionally some passengers are involuntarily bumped from the flight. Obviously, these incidents can reflect poorly on customer satisfaction. Suppose Southwest Airlines would like to estimate the true proportion of involuntarily bumped passengers across all domestic flights in the industry. In a pilot sample of 618 domestic passengers, 267 were involuntarily bumped. What is the estimate of the population proportion and what is the standard error of this estimate?

Question 1 options:

1)	The true population proportion is needed to calculate this.

2)	Estimate of proportion: 0.432, Standard error: 0.0008.

3)	Estimate of proportion: 0.568, Standard error: 0.0008.

4)	Estimate of proportion: 0.568, Standard error: 0.0199.

5)	Estimate of proportion: 0.432, Standard error: 0.0199.

Question 2 (1 point)

109 employees of your firm were asked about their job satisfaction. Out of the 109, 43 said they were unsatisfied. What is the estimate of the population proportion? What is the standard error of this estimate?

Question 2 options:

1)	The true population proportion is needed to calculate this.

2)	Estimate of proportion: 0.606, Standard error: 0.0045.

3)	Estimate of proportion: 0.606, Standard error: 0.0468.

4)	Estimate of proportion: 0.394, Standard error: 0.0468.

5)	Estimate of proportion: 0.394, Standard error: 0.0045.

Question 3 (1 point)

A sample proportion is calculated from a sample size of 366. How large of a sample would we need in order to decrease the standard error by a factor of 7?

Question 3 options:

1)

2,562

2)

6,222

3)

968

4)

17,934

5)

11,346

Question 4 (1 point)

Historically, 76.95% of packages delivered by UPS are on time. Suppose 103 deliveries are randomly selected for quality control. What is the probability that less than 69.34% of the deliveries were on time?

Question 4 options:

1)

0.9667

2)

1.7891

3)

0.5000

4)

0.0333

5)

<0.0001

Answer 1