On a given MCO-ATL flight, there are 200 seats and each seat is sold at an average ticket price of 300. It has been observed that on most days in the past month, the flight rarely approaches 100% occupancy since there are passenger no-shows. Hence, the airline decides to overbook flights. The airline manager assigned the task of determining the number of seats to overbook on this flight estimates: (a) no-shows using historical information; and (b) service denial rate the airline should offer if on a specific day a customer is denied a seat due to overbookings. However, she encounters an interesting conundrum: Both the mean and std. deviation of no-shows changes based on the service denial rate offered. This leads the manager to consider alternative overbooking strategies with each one corresponding to the possible different service denial rates. No-show data for each service denial rate are:

1. Service Denial Rate of $ 400 in this case, no-shows are normally distributed with a mean of 30 and standard deviation of 8.

2. Service Denial Rate of $ 450 in this case, no-shows are normally distributed with a mean of 25 and standard deviation of 6.

3. Service Denial Rate of $ 500 in this case, no-shows are normally distributed with a mean of 20 and standard deviation of 4. You are required to assist the store manager in completing the table below.

Service Denial Rate Optimal Percentage Overbooks of time Y* customers will be bumped Expected loss ($) through bumping passengers Expected loss ($) for empty seats $ 400 $ 450 $ 500 Service Denial Rate Optimal Percentage Overbooks of time Y* customers will be bumped Expected loss ($) through bumping passengers Expected loss ($) for empty seats $ 400 $ 450 $ 500