mba 522 Poisson Distribution

mba 522 Poisson Distribution - But it is crucial to...

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Poisson Distribution Keep in mind that Poisson distribution describes number of occurrences in an interval (of space or time). Example, it could be that we are concerned about: number of calls received at a call center in 30 minutes. number of e-mails received by a server in 15 minutes. number of customers arriving at a restaurant in one hour. number of cars entering a drive-up teller window in 10 minutes. number of defects in a 100-yard piece of cloth. number of bubbles in a 5-feet piece of glass, etc. What is important, is that you must have mu (the average number of occurrences in a certain interval). Then you can use that in the formula to calculate probability of X.
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Unformatted text preview: But it is crucial to remember that the mu must be stated in the same interval as the X being used in the formula. For example, let us say: mu=5 customers arriving at a McDonald's in 10 minutes, But you want to calculate probability that no one arrives in a 15 minute interval. Since mu is in terms of 10 minutes, you must first convert it to 15 minute intervals before computing probability of X=0 in 15 minutes! So: if mu=5 per 10 minutes, then we can compute: mu=7.5 per 15 minutes. Now that we have mu expressed per 15 minutes, we can solve probability of X=0 in 15 minutes: P(0)=[(7.5^0)(e^-7.5)]/0!...
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