Probability Poisson Process and Gamma Distribution

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Saladsamurai
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Homework Statement



Textbook problem 6.56 text: the number of automobiles arriving per minute at an intersection is Poisson with mean 5; (a) probability more than 10 automobiles in a minute; (b) probability more than 2 minutes before 10 cars arrive.



The Attempt at a Solution



Part (a) is no problem, it is simply P(X>10) = 1 - P(X<=10) which requires the use of tabulated cumulative poisson values.

Part (b) is throwing for a loop. I know that I need to invoke the Gamma distribution since that is what the solution is doing. But I don't really understand why. I think that it is because there is some relationship between a Poisson process and the Gamma distribution, but I am not exactly sure what it is.

What I do know, is that for Poisson processes, the probability that an event occurs X = x number of times in 't' time depends on the average number of times the Poisson event occurs per unit time. But how can I use this knowledge to solve part (b)?

Any thoughts?
Casey



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Here is the solution if it helps to generate any ideas. I am just not sure why they are using the Gamma distribution.

Handwritten-style typeset solution to a gamma distribution problem: P(X > 2) computed via a gamma integral with beta = 1/5, alpha = 10, giving 1 - 0.542 = 0.458.
 
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Any thoughts on this one? For some reason, I feel like it would make more sense to use the exponential distribution, but again, I am not really sure why. I still don't see why the fact that it is a poisson process allows me to infer that I can or should be using a gamma distribution?