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Poisson vs binomial process

  1. Feb 29, 2012 #1
    I might need you guys to help me see how this proces, will be distributed:

    Suppose we have a large amount of elements N(≈1012). I'm simulating a system where I for each iteration damage a random element. If an element gets damaged its damagecounter goes up 1.
    So say I pick element number 100123 on the first iteration. Its damagecounter will now count +1 whilst the damagecounters of the other elements in the system will be 0.

    I want to write an expression for the probability that a specific element acquires k damages in t iterations. Here are my steps in deriving an expression:

    1) The probability for a specific element to get damaged must be 1/N.

    2) Thus the probability that a specific element gets k damages after t iterations must be:

    p(x=k) = K(t,k) * (1/N)k * (1-1/N)t-k

    where K(t,k) denotes the binomial coefficient.

    Now, I want to find the total probability for an element to have acquired k damages during our t iterations. Thus I multiply by N and end up with:

    p(x=k) = N * K(t,k) * (1/N)k * (1-1/N)t-k

    Now first of all, I want to know: Would this expression be correct or am I making any mistakes/illegal assumptions in the derivation?

    Second, my model appears to follow a poisson distribution, when I plot the amount of elements with damage 1->10 versus time. Does that fit with this theory? I can't quite see if that is a good thing or not?
    Last edited: Feb 29, 2012
  2. jcsd
  3. Feb 29, 2012 #2


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    Science Advisor

    I won't comment on your derivation.

    However, in general, Poisson distribution is a good approximation for the binomial for large N and Np fixed.
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