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Thread: Solving contrived word problems with Discrete Distributions.

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    Solving contrived word problems with Discrete Distributions.

    Hi,
    feel free to add comments, critique, or criticize my view on these distributions.


    We use discrete uniform to solve problems when we are given equally likely outcomes.


    We use binomial distribution to solve problems where we want to know how many X successes there are out of n trials.

    We use hyper geometric distribution when ? I am not sure.

    We use geometric distribution :
    Trials X: to find the number of trial on which x success occurs.
    Failures Y: To find the number of failures until x success occurs.

    Negative binomial distribution:
    Trials X: to find the number of trial on which r-th success occurs.
    Failures Y: to find the number of failures until r-th success occurs.'

    Poisson distribution: Is usually a certain type of events related to a certain set of time interval.
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  2. #2
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    Re: Solving contrived word problems with Discrete Distributions.

    Quote Originally Posted by math951 View Post
    Hi,
    feel free to add comments, critique, or criticize my view on these distributions.


    We use discrete uniform to solve problems when we are given equally likely outcomes.

    We use binomial distribution to solve problems where we want to know how many X successes there are out of n trials.

    We use hyper geometric distribution when ? I am not sure.
    Hypergeometric similar to the Binomial distribution but it's k successes out of n w/o replacement

    We use geometric distribution :
    Trials X: to find the number of trial on which x success occurs.
    Failures Y: To find the number of failures until x success occurs.

    Negative binomial distribution:
    Trials X: to find the number of trial on which r-th success occurs.
    Failures Y: to find the number of failures until r-th success occurs.'

    Poisson distribution: Is usually a certain type of events related to a certain set of time interval.
    Poisson distribution models the number of events that actually occur in a time period given an average rate of occurrence.
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