Section7Notes - OR360 Section 7 Notes Common Continuous...

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OR360 Section 7 Notes Common Continuous Distributions 1 Exponential Distribution Recall an exponentially distributed random variable X has density: f X ( x ) = λe - λx , x 0 , for some parameter λ > 0. It has cumulative distribution F X ( x ) = 1 - e - λx . The moment generating function can be computed: φ ( t ) = E ± e tX ² = Z 0 e tx λe - λx dx = λ λ - t Z 0 ( λ - t ) e - ( λ - t ) x dx = λ λ - t . We have previously shown the memorylessness property: P { X > s + t | X > t } = P { X > s } , for s, t 0 . Example: In a post office with two clerks, Alice and Bob are being served, when Charlie walks in. Charlie’s service will begin when either Alice or Bob leave. Suppose each service time is exponentially distributed with parameter λ . What is the probability that Charlie is the last to leave? Solution: Let t be the time that either Alice or Bob leaves (suppose Alice leaves), and let X be Bob’s total service time. Then P { X > s + t | X > t } = P { X > s } , so the remaining service time is still exponentially distributed with parameter λ . That is, it’s as if Bob were starting his service all over again at the time that Charlie’s service starts. Thus, by symmetry, the probability that Bob finishes before Charlie is 1 2 . Example:
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This note was uploaded on 09/22/2009 for the course ORIE 3500 taught by Professor Weber during the Summer '08 term at Cornell University (Engineering School).

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Section7Notes - OR360 Section 7 Notes Common Continuous...

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