Question

Airline seats can be either discretionary or essential. For most people, the price you pay for where you sit on the plane is a discretionary expense. The seat map for a particular flight is shown here.

There are a total of 149 seats on this flight. Although seating prices change based on a number of factors, answer the questions below based on the prices listed above.

1. Using the attached document, construct a frequency distribution table with column headings "Seat Type," "Price," and "Number of Seats."

2. If all seats were sold on this flight, what would be the total airline income for the seats?

3. Determine the mean, median, and mode seat prices. Round to the nearest cent.

Mean:
Median:
Mode:

Answer 1

Without specific pricing data for airline seats, frequency distribution cannot be created, nor can total income be calculated. The mean number of unoccupied seats and sample standard deviation provided cannot be used to calculate mean, median, mode without additional data. Hypothesis testing for railroad's travel distance and ticket class would require a chi-squared test, which cannot be conducted without the actual data.

Step-by-step explanation:

The question requires us to perform several statistical analyses regarding airline seats and passenger travel choices, but due to the lack of specific pricing data for the seat types in the provided information, an exact frequency distribution table cannot be constructed nor can the total income for the airline seats be calculated. However, we can answer conceptually based on the information given about the airline wanting to estimate its mean number of unoccupied seats per flight. With a sample mean of 11.6 and a sample standard deviation of 4.1 for 225 flights, we might typically use these to construct confidence intervals or perform hypothesis testing regarding the airline's unoccupied seats.

As for the railroad's interest in the relationship between travel distance and ticket class purchased, this involves conducting a chi-squared test for independence where the expected values for each category would be computed based on the sample data and then compared against the observed counts to calculate the test statistic and p-value. Unfortunately, without the actual data from Table 11.31, we cannot calculate these values but could provide a conceptual explanation and methodology for the analysis.