S23.2 Poisson Arrivals During an Exponential Interval

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MIT RES.6-012 Introduction to Probability, Spring 2018
Instructor: John Tsitsiklis

License: Creative Commons BY-NC-SA
  1. MIT OpenCourseWare
  2. Poisson Arrivals
  3. Exponential Interval
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Комментарии
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Shouldn't the formula be lambda*t at 2:21

fu
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The integral is gamma function, so will integrate to k factorial, and cancel out the k! in the denominator.

魏寅生
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3:05 why isn't it just lambda^k* mu / ( (lambda+mu)* k! ) ?

dlisetteb
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What is the resolution of this exercise:

Consider a queuing model with two attendants and a waiting position operating under steady-state conditions. Suppose that if a customer arrives and finds both agents busy and the waiting position unoccupied, then the customer will wait as long as necessary for service. If the customer finds both attendants busy and the waiting position also occupied, he leaves immediately.

Customers access the system according to a Poisson process with a rate of 2 customers per hour and that service follows an exponential distribution with a mean of 1 hour. The proportion of customers who arrive at the system and will not be served is:

a)2/5 b)1/8 c)2/3 d)2/7 e)1/6

analisecritica