Yellow Airlines operates a flight from Dallas to Boston. Two fares are offered a low fare of $175 and a high fare of $550. Low-fare demand books before high-fare demand, and there is ample demand at the low fare. Demand for the high fare is estimated to be normal with a mean of 35 and a standard deviation of 20. If the flight has 90 coach seats, what is the optimal number of seats that should be reserved for the high fare?
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
Q. Yellow Airlines operates a flight from Dallas to Boston. Two fares are offered a low fare of $175 and a high fare of $550. Low-fare demand books before high-fare demand, and there is ample demand at the low fare. Demand for the high fare is estimated to be normal with a mean of 35 and a standard deviation of 20. If the flight has 90 coach seats, what is the optimal number of seats that should be reserved for the high fare?
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