Simple formula for Bayesian updating

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I am given a biased coin, which I'm told will give Heads with a probability of "about" $p$ (prior probability?).



Now if I flip the coin $n$ times and get $h$ Heads, is there a simple formula to give me a revised estimate of the probability $p$ (posterior probability?) according to Bayes theorem?



Presumably, the more times I flip the coin (the greater is $n$), the greater the potential change in my estimate of $p$, but I'm not sure how to calculate this.



Any help would be much appreciated, thanks.




statistical-inference bayesian bayes-theorem




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    up vote
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    I am given a biased coin, which I'm told will give Heads with a probability of "about" $p$ (prior probability?).



    Now if I flip the coin $n$ times and get $h$ Heads, is there a simple formula to give me a revised estimate of the probability $p$ (posterior probability?) according to Bayes theorem?



    Presumably, the more times I flip the coin (the greater is $n$), the greater the potential change in my estimate of $p$, but I'm not sure how to calculate this.



    Any help would be much appreciated, thanks.




    statistical-inference bayesian bayes-theorem




    share|cite|improve this question





















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      up vote
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      down vote

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      I am given a biased coin, which I'm told will give Heads with a probability of "about" $p$ (prior probability?).



      Now if I flip the coin $n$ times and get $h$ Heads, is there a simple formula to give me a revised estimate of the probability $p$ (posterior probability?) according to Bayes theorem?



      Presumably, the more times I flip the coin (the greater is $n$), the greater the potential change in my estimate of $p$, but I'm not sure how to calculate this.



      Any help would be much appreciated, thanks.




      statistical-inference bayesian bayes-theorem




      share|cite|improve this question











      I am given a biased coin, which I'm told will give Heads with a probability of "about" $p$ (prior probability?).



      Now if I flip the coin $n$ times and get $h$ Heads, is there a simple formula to give me a revised estimate of the probability $p$ (posterior probability?) according to Bayes theorem?



      Presumably, the more times I flip the coin (the greater is $n$), the greater the potential change in my estimate of $p$, but I'm not sure how to calculate this.



      Any help would be much appreciated, thanks.





      statistical-inference bayesian bayes-theorem





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      share|cite|improve this question




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      asked Jul 23 at 21:08









      Kelvin

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