Delta Airlines quotes a flight time of 2 hours, 10 minutes for its flights from Cincinnati to Tampa. Suppose we believe that actual flight times are uniformly distributed between 2 hours and 2 hours, 30 minutes. (a) Show the graph of the probability density function for flight time. (b) What is the probability that the flight will be no more than 5 minutes late? (c) What is the probability that the flight will be more than 10 minutes late? (d) What is the expected flight time? What is the variance of the flight time?
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!
Delta Airlines quotes a flight time of 2 hours, 10 minutes for its flights from Cincinnati to Tampa. Suppose we believe that actual flight times are uniformly distributed between 2 hours and 2 hours, 30 minutes.
(a) Show the graph of the
(b) What is the probability that the flight will be no more than 5 minutes late? (c) What is the probability that the flight will be more than 10 minutes late? (d) What is the expected flight time? What is the variance of the flight time?
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