Airline passengers arrive randomly and independently at the passenger-screening facility at a major international airport. The mean arrival rate is 5 passengers per minute. (a). Compute the probability of one arrival in a one-minute period. (b). Compute the probability that two or more passengers arrive in a one-minute period. (c). Compute the probability of no arrivals in a 12-second period. (d). Compute the probability of at least one arrival in a 12-second perioD
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!
Airline passengers arrive randomly and independently at the passenger-screening facility at a major international airport. The mean arrival rate is 5 passengers per minute.
(a). Compute the probability of one arrival in a one-minute period.
(b). Compute the probability that two or more passengers arrive in a one-minute period.
(c). Compute the probability of no arrivals in a 12-second period.
(d). Compute the probability of at least one arrival in a 12-second perioD
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