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Poisson distribution

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Uploaded by on Jan 21, 2008

The Poisson is a classic distribution used in operational risk. It often fits (describes) random variables over time intervals. For example, it might try to characterize the number of low severity, high frequency (HFLS) loss events over a month or a year. It is a discrete function that conveniently only needs one parameter: lambda, which is both the mean and the variance.

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  • Incredibly helpful video! Thanks for your time!

  • @faYte0607 lamda = n * p

    n=100

    p=0.05

  • Thanks very much for an excellent explanation. Really helpful.

  • You should really explain how you got the lamda number 5 in the first problem...

  • your explanation made me so confortable for this distriibution.

  • Best explain had ! Thanks

  • You are amazing. I wish you were my Professor.

  • im not exactly sure. its about the scope of the values you have. i think if its a number of events PER greater event, you use the poisson. like number of typos PER page in a book. or number of craters PER square mile of the moon. or number of car accidents PER road in manhattan.

  • Hey, I just wanted to know when I should use the Poisson, and when I should use the Counting Rules for Combination? Or are they the same?

    I found that they give about the same value: though I could be doing them both wrong.

    Does anyone know?

  • Given that we're examining 100 objects it wouldn't be .05 of those. It would be 5.

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