The expectation of a geometric random variable where its parameter is uniform











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First thanks for any help editing my text.



If a random variable $X$ has a geometric distribution with parameter $P$ where $P$ itself is a random variable and uniformly distributed from $0$ to $1-1/n$, I want to find $E[X]$.



I first learned that $E[X|P] = 1/P$, using the expectation of the geometric distribution.



But when it comes to $E[X]=E[E[X|P]]$, I tried integration and it seems to be



(integral from $0$ to $(n-1)/n$) , $(1/p)$ * $(n/(n-1))$ $dp$



but isn't the value infinite?










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  • I think you are right.
    – Kavi Rama Murthy
    Nov 19 at 7:45










  • Yes; were you expecting it to be finite or any particular reason?
    – Aditya Dua
    Nov 20 at 7:15















up vote
1
down vote

favorite












First thanks for any help editing my text.



If a random variable $X$ has a geometric distribution with parameter $P$ where $P$ itself is a random variable and uniformly distributed from $0$ to $1-1/n$, I want to find $E[X]$.



I first learned that $E[X|P] = 1/P$, using the expectation of the geometric distribution.



But when it comes to $E[X]=E[E[X|P]]$, I tried integration and it seems to be



(integral from $0$ to $(n-1)/n$) , $(1/p)$ * $(n/(n-1))$ $dp$



but isn't the value infinite?










share|cite|improve this question
























  • I think you are right.
    – Kavi Rama Murthy
    Nov 19 at 7:45










  • Yes; were you expecting it to be finite or any particular reason?
    – Aditya Dua
    Nov 20 at 7:15













up vote
1
down vote

favorite









up vote
1
down vote

favorite











First thanks for any help editing my text.



If a random variable $X$ has a geometric distribution with parameter $P$ where $P$ itself is a random variable and uniformly distributed from $0$ to $1-1/n$, I want to find $E[X]$.



I first learned that $E[X|P] = 1/P$, using the expectation of the geometric distribution.



But when it comes to $E[X]=E[E[X|P]]$, I tried integration and it seems to be



(integral from $0$ to $(n-1)/n$) , $(1/p)$ * $(n/(n-1))$ $dp$



but isn't the value infinite?










share|cite|improve this question















First thanks for any help editing my text.



If a random variable $X$ has a geometric distribution with parameter $P$ where $P$ itself is a random variable and uniformly distributed from $0$ to $1-1/n$, I want to find $E[X]$.



I first learned that $E[X|P] = 1/P$, using the expectation of the geometric distribution.



But when it comes to $E[X]=E[E[X|P]]$, I tried integration and it seems to be



(integral from $0$ to $(n-1)/n$) , $(1/p)$ * $(n/(n-1))$ $dp$



but isn't the value infinite?







probability-distributions conditional-expectation uniform-distribution expected-value






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Nov 19 at 8:03

























asked Nov 19 at 7:40









Richard

426




426












  • I think you are right.
    – Kavi Rama Murthy
    Nov 19 at 7:45










  • Yes; were you expecting it to be finite or any particular reason?
    – Aditya Dua
    Nov 20 at 7:15


















  • I think you are right.
    – Kavi Rama Murthy
    Nov 19 at 7:45










  • Yes; were you expecting it to be finite or any particular reason?
    – Aditya Dua
    Nov 20 at 7:15
















I think you are right.
– Kavi Rama Murthy
Nov 19 at 7:45




I think you are right.
– Kavi Rama Murthy
Nov 19 at 7:45












Yes; were you expecting it to be finite or any particular reason?
– Aditya Dua
Nov 20 at 7:15




Yes; were you expecting it to be finite or any particular reason?
– Aditya Dua
Nov 20 at 7:15















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