Probability of P(X $le$ U $le$ Y ) of random independed variables [closed]












1












$begingroup$


X; Y; U are random independent variables. X; Y are exponential distributed
with $lambda$ and U $sim$ Uni[0; 1].
How i find the probability:
P(X $le$ U $le$ Y )



Thanks










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closed as off-topic by Davide Giraudo, Paul Frost, Shailesh, KReiser, mrtaurho Jan 6 at 0:43


This question appears to be off-topic. The users who voted to close gave this specific reason:


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    1












    $begingroup$


    X; Y; U are random independent variables. X; Y are exponential distributed
    with $lambda$ and U $sim$ Uni[0; 1].
    How i find the probability:
    P(X $le$ U $le$ Y )



    Thanks










    share|cite|improve this question









    $endgroup$



    closed as off-topic by Davide Giraudo, Paul Frost, Shailesh, KReiser, mrtaurho Jan 6 at 0:43


    This question appears to be off-topic. The users who voted to close gave this specific reason:


    • "This question is missing context or other details: Please provide additional context, which ideally explains why the question is relevant to you and our community. Some forms of context include: background and motivation, relevant definitions, source, possible strategies, your current progress, why the question is interesting or important, etc." – Davide Giraudo, Paul Frost, Shailesh, KReiser, mrtaurho

    If this question can be reworded to fit the rules in the help center, please edit the question.



















      1












      1








      1





      $begingroup$


      X; Y; U are random independent variables. X; Y are exponential distributed
      with $lambda$ and U $sim$ Uni[0; 1].
      How i find the probability:
      P(X $le$ U $le$ Y )



      Thanks










      share|cite|improve this question









      $endgroup$




      X; Y; U are random independent variables. X; Y are exponential distributed
      with $lambda$ and U $sim$ Uni[0; 1].
      How i find the probability:
      P(X $le$ U $le$ Y )



      Thanks







      probability probability-distributions






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      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked Jan 5 at 17:29









      Merlin71Merlin71

      82




      82




      closed as off-topic by Davide Giraudo, Paul Frost, Shailesh, KReiser, mrtaurho Jan 6 at 0:43


      This question appears to be off-topic. The users who voted to close gave this specific reason:


      • "This question is missing context or other details: Please provide additional context, which ideally explains why the question is relevant to you and our community. Some forms of context include: background and motivation, relevant definitions, source, possible strategies, your current progress, why the question is interesting or important, etc." – Davide Giraudo, Paul Frost, Shailesh, KReiser, mrtaurho

      If this question can be reworded to fit the rules in the help center, please edit the question.







      closed as off-topic by Davide Giraudo, Paul Frost, Shailesh, KReiser, mrtaurho Jan 6 at 0:43


      This question appears to be off-topic. The users who voted to close gave this specific reason:


      • "This question is missing context or other details: Please provide additional context, which ideally explains why the question is relevant to you and our community. Some forms of context include: background and motivation, relevant definitions, source, possible strategies, your current progress, why the question is interesting or important, etc." – Davide Giraudo, Paul Frost, Shailesh, KReiser, mrtaurho

      If this question can be reworded to fit the rules in the help center, please edit the question.






















          1 Answer
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          $begingroup$

          For given positive real numbers $xleq yleq 1$, we have that
          $
          mathbb P(xleq Uleq y)=y-x,
          $

          whereas if $xleq 1leq y$ we have $mathbb P(xleq Uleq y)=1-x$, and otherwise this quantity is zero. Therefore



          $$mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1leq Y].$$
          Since $X$ and $Y$ are independent, this simplifies to
          $$
          mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1] cdot mathbb P(Ygeq 1).
          $$

          The second term is easy to calculate, since $mathbb P(Ygeq 1)=e^{-lambda}$ by definition and
          $$
          mathbb E[1-X; Xleq 1] =int_{0}^1(1-x) lambda e^{-lambda x} dx=1+frac{e^{-lambda}-1}{lambda}.
          $$

          For the first term, we have
          $$begin{align*}
          mathbb E[Y-X; Xleq Yleq 1]&=int_0^1int_0^y(y-x) lambda^2 e^{-lambda(x+y)} dx dy\
          &=int_0^1 e^{-lambda y}(lambda y-1)+e^{-2lambda y} dy\
          &=frac{1-e^{-2lambda}}{2lambda}-e^{-lambda}.
          end{align*}$$

          Therefore
          $$
          mathbb P(Xleq Uleq Y)=frac{1-e^{-2lambda}}{2lambda}+e^{-lambda}cdot frac{e^{-lambda}-1}{lambda}=frac{(1-e^{-lambda})^2}{2lambda}.
          $$






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            1 Answer
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            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            0












            $begingroup$

            For given positive real numbers $xleq yleq 1$, we have that
            $
            mathbb P(xleq Uleq y)=y-x,
            $

            whereas if $xleq 1leq y$ we have $mathbb P(xleq Uleq y)=1-x$, and otherwise this quantity is zero. Therefore



            $$mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1leq Y].$$
            Since $X$ and $Y$ are independent, this simplifies to
            $$
            mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1] cdot mathbb P(Ygeq 1).
            $$

            The second term is easy to calculate, since $mathbb P(Ygeq 1)=e^{-lambda}$ by definition and
            $$
            mathbb E[1-X; Xleq 1] =int_{0}^1(1-x) lambda e^{-lambda x} dx=1+frac{e^{-lambda}-1}{lambda}.
            $$

            For the first term, we have
            $$begin{align*}
            mathbb E[Y-X; Xleq Yleq 1]&=int_0^1int_0^y(y-x) lambda^2 e^{-lambda(x+y)} dx dy\
            &=int_0^1 e^{-lambda y}(lambda y-1)+e^{-2lambda y} dy\
            &=frac{1-e^{-2lambda}}{2lambda}-e^{-lambda}.
            end{align*}$$

            Therefore
            $$
            mathbb P(Xleq Uleq Y)=frac{1-e^{-2lambda}}{2lambda}+e^{-lambda}cdot frac{e^{-lambda}-1}{lambda}=frac{(1-e^{-lambda})^2}{2lambda}.
            $$






            share|cite|improve this answer









            $endgroup$


















              0












              $begingroup$

              For given positive real numbers $xleq yleq 1$, we have that
              $
              mathbb P(xleq Uleq y)=y-x,
              $

              whereas if $xleq 1leq y$ we have $mathbb P(xleq Uleq y)=1-x$, and otherwise this quantity is zero. Therefore



              $$mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1leq Y].$$
              Since $X$ and $Y$ are independent, this simplifies to
              $$
              mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1] cdot mathbb P(Ygeq 1).
              $$

              The second term is easy to calculate, since $mathbb P(Ygeq 1)=e^{-lambda}$ by definition and
              $$
              mathbb E[1-X; Xleq 1] =int_{0}^1(1-x) lambda e^{-lambda x} dx=1+frac{e^{-lambda}-1}{lambda}.
              $$

              For the first term, we have
              $$begin{align*}
              mathbb E[Y-X; Xleq Yleq 1]&=int_0^1int_0^y(y-x) lambda^2 e^{-lambda(x+y)} dx dy\
              &=int_0^1 e^{-lambda y}(lambda y-1)+e^{-2lambda y} dy\
              &=frac{1-e^{-2lambda}}{2lambda}-e^{-lambda}.
              end{align*}$$

              Therefore
              $$
              mathbb P(Xleq Uleq Y)=frac{1-e^{-2lambda}}{2lambda}+e^{-lambda}cdot frac{e^{-lambda}-1}{lambda}=frac{(1-e^{-lambda})^2}{2lambda}.
              $$






              share|cite|improve this answer









              $endgroup$
















                0












                0








                0





                $begingroup$

                For given positive real numbers $xleq yleq 1$, we have that
                $
                mathbb P(xleq Uleq y)=y-x,
                $

                whereas if $xleq 1leq y$ we have $mathbb P(xleq Uleq y)=1-x$, and otherwise this quantity is zero. Therefore



                $$mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1leq Y].$$
                Since $X$ and $Y$ are independent, this simplifies to
                $$
                mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1] cdot mathbb P(Ygeq 1).
                $$

                The second term is easy to calculate, since $mathbb P(Ygeq 1)=e^{-lambda}$ by definition and
                $$
                mathbb E[1-X; Xleq 1] =int_{0}^1(1-x) lambda e^{-lambda x} dx=1+frac{e^{-lambda}-1}{lambda}.
                $$

                For the first term, we have
                $$begin{align*}
                mathbb E[Y-X; Xleq Yleq 1]&=int_0^1int_0^y(y-x) lambda^2 e^{-lambda(x+y)} dx dy\
                &=int_0^1 e^{-lambda y}(lambda y-1)+e^{-2lambda y} dy\
                &=frac{1-e^{-2lambda}}{2lambda}-e^{-lambda}.
                end{align*}$$

                Therefore
                $$
                mathbb P(Xleq Uleq Y)=frac{1-e^{-2lambda}}{2lambda}+e^{-lambda}cdot frac{e^{-lambda}-1}{lambda}=frac{(1-e^{-lambda})^2}{2lambda}.
                $$






                share|cite|improve this answer









                $endgroup$



                For given positive real numbers $xleq yleq 1$, we have that
                $
                mathbb P(xleq Uleq y)=y-x,
                $

                whereas if $xleq 1leq y$ we have $mathbb P(xleq Uleq y)=1-x$, and otherwise this quantity is zero. Therefore



                $$mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1leq Y].$$
                Since $X$ and $Y$ are independent, this simplifies to
                $$
                mathbb P(Xleq Uleq Y)=mathbb E[Y-X; Xleq Yleq 1] + mathbb E[1-X; Xleq 1] cdot mathbb P(Ygeq 1).
                $$

                The second term is easy to calculate, since $mathbb P(Ygeq 1)=e^{-lambda}$ by definition and
                $$
                mathbb E[1-X; Xleq 1] =int_{0}^1(1-x) lambda e^{-lambda x} dx=1+frac{e^{-lambda}-1}{lambda}.
                $$

                For the first term, we have
                $$begin{align*}
                mathbb E[Y-X; Xleq Yleq 1]&=int_0^1int_0^y(y-x) lambda^2 e^{-lambda(x+y)} dx dy\
                &=int_0^1 e^{-lambda y}(lambda y-1)+e^{-2lambda y} dy\
                &=frac{1-e^{-2lambda}}{2lambda}-e^{-lambda}.
                end{align*}$$

                Therefore
                $$
                mathbb P(Xleq Uleq Y)=frac{1-e^{-2lambda}}{2lambda}+e^{-lambda}cdot frac{e^{-lambda}-1}{lambda}=frac{(1-e^{-lambda})^2}{2lambda}.
                $$







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                answered Jan 5 at 19:33









                pre-kidneypre-kidney

                12.8k1748




                12.8k1748















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