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mba 522 relationship_Poisson_exponential_

# mba 522 relationship_Poisson_exponential_ - 6 a.m 7 a.m...

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Consider the graph presented above, which represents number of e-mails I received between 6 a.m. and 7 a.m. Each arrow is an e-mail (an occurrence). The number of e-mails received in the one hour period (occurrences in a 1-hr interval) is a Poisson variable, which is discrete and countable. The time between the e-mails received (segment of the line between arrows) is an exponential variable, which is continuous and measurable. Understanding the relationship between Poisson and Exponential Distributions using an Example Problem statement: According to Barron’s 1998 Primary Reader Survey, the average annual number of investment transactions for a subscriber is 30 ( www.barronsmag.com , July 28, 2000). Suppose the number of transactions in a year follows the Poisson probability distribution. A. Show the probability distribution for the time between investment transactions. B. What is the probability of no transactions during the month of January for a particular subscriber?

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