Probability Poisson Process and Gamma Distribution

In summary, the conversation discusses two parts of a problem, with part (a) being straightforward and part (b) requiring the use of the Gamma distribution. The individual is unsure of the relationship between the Poisson process and the Gamma distribution, but understands that the probability of events occurring in a given time period is related to the average number of occurrences per unit time. The solution provided uses the Gamma distribution, but the individual is unsure why and suggests using the exponential distribution instead.
  • #1
Saladsamurai
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Homework Statement



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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.

Screenshot2010-06-16at120204AM.png
 
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  • #2
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?
 

FAQ: Probability Poisson Process and Gamma Distribution

1. What is a Poisson process?

A Poisson process is a type of stochastic process that models the occurrence of rare events over time or space. It is based on the assumption that these events occur independently and at a constant rate. The number of events that occur in a given time interval follows a Poisson distribution.

2. How is probability related to a Poisson process?

In a Poisson process, the probability of a certain number of events occurring in a given time interval can be calculated using the Poisson distribution. This distribution takes into account the rate of occurrence of events and the length of the time interval.

3. What is the difference between a Poisson process and a Poisson distribution?

A Poisson process is a stochastic process that models the occurrence of events over time or space, while a Poisson distribution is a probability distribution that describes the likelihood of a certain number of events occurring in a given time interval in a Poisson process.

4. What is a gamma distribution?

A gamma distribution is a continuous probability distribution that is often used to model the time between events in a Poisson process. It is characterized by two parameters, shape and scale, and is commonly used in areas such as survival analysis and reliability.

5. How are gamma distributions and Poisson processes related?

In a Poisson process, the time between events follows a gamma distribution. This means that the probability of a certain amount of time passing between events can be calculated using the parameters of the gamma distribution. Additionally, the sum of independent gamma-distributed random variables follows a gamma distribution, which can be useful in modeling certain types of Poisson processes.

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