Conditional Expectation of joint pdf

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Wish to identify what I'm doing wrong when finding the E(X|Y=5) of the following:
$$f(x, y)=begincases
1/6 & textif 0<x<2, 0<y<6-3x \ 0 & textotherwise
&
endcases.$$



My working:
$$beginalignmathsf E(Xmid Y=5)~&=~displaystyleint_0^2 x fracfrac16f(y),mathsf d xendalign$$
where
$$beginalignmathsf f(y)~&=~displaystyleint_0^frac-y+63 frac16 ,mathsf d x = frac6-y18endalign$$



Therefore,
$$beginalignmathsf E(Xmid Y=5)~&=~displaystyleint_0^2 x fracfrac16frac6-y18,mathsf d x mathsf ~&=~displaystyleint_0^2 x fracfrac16frac6-518,mathsf d x~&=~displaystyleint_0^2 3x ,mathsf d x endalign = 6$$



But then when I compute Var(X|Y=5), the answer is getting negative, which is impossible. So I think that I might have done something wrong when calculating the expectation.



My working for Variance:
$$Var(X|Y=5) = E(X^2|Y=5) - (E(X|Y=5) )^2 = 8 - 6^2 = -28$$



I appreciate any help.










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  • you forgot the constraint on the support of $X$ given $Y=y.$
    – Xi'an
    33 mins ago
















up vote
3
down vote

favorite












Wish to identify what I'm doing wrong when finding the E(X|Y=5) of the following:
$$f(x, y)=begincases
1/6 & textif 0<x<2, 0<y<6-3x \ 0 & textotherwise
&
endcases.$$



My working:
$$beginalignmathsf E(Xmid Y=5)~&=~displaystyleint_0^2 x fracfrac16f(y),mathsf d xendalign$$
where
$$beginalignmathsf f(y)~&=~displaystyleint_0^frac-y+63 frac16 ,mathsf d x = frac6-y18endalign$$



Therefore,
$$beginalignmathsf E(Xmid Y=5)~&=~displaystyleint_0^2 x fracfrac16frac6-y18,mathsf d x mathsf ~&=~displaystyleint_0^2 x fracfrac16frac6-518,mathsf d x~&=~displaystyleint_0^2 3x ,mathsf d x endalign = 6$$



But then when I compute Var(X|Y=5), the answer is getting negative, which is impossible. So I think that I might have done something wrong when calculating the expectation.



My working for Variance:
$$Var(X|Y=5) = E(X^2|Y=5) - (E(X|Y=5) )^2 = 8 - 6^2 = -28$$



I appreciate any help.










share|cite|improve this question























  • you forgot the constraint on the support of $X$ given $Y=y.$
    – Xi'an
    33 mins ago












up vote
3
down vote

favorite









up vote
3
down vote

favorite











Wish to identify what I'm doing wrong when finding the E(X|Y=5) of the following:
$$f(x, y)=begincases
1/6 & textif 0<x<2, 0<y<6-3x \ 0 & textotherwise
&
endcases.$$



My working:
$$beginalignmathsf E(Xmid Y=5)~&=~displaystyleint_0^2 x fracfrac16f(y),mathsf d xendalign$$
where
$$beginalignmathsf f(y)~&=~displaystyleint_0^frac-y+63 frac16 ,mathsf d x = frac6-y18endalign$$



Therefore,
$$beginalignmathsf E(Xmid Y=5)~&=~displaystyleint_0^2 x fracfrac16frac6-y18,mathsf d x mathsf ~&=~displaystyleint_0^2 x fracfrac16frac6-518,mathsf d x~&=~displaystyleint_0^2 3x ,mathsf d x endalign = 6$$



But then when I compute Var(X|Y=5), the answer is getting negative, which is impossible. So I think that I might have done something wrong when calculating the expectation.



My working for Variance:
$$Var(X|Y=5) = E(X^2|Y=5) - (E(X|Y=5) )^2 = 8 - 6^2 = -28$$



I appreciate any help.










share|cite|improve this question















Wish to identify what I'm doing wrong when finding the E(X|Y=5) of the following:
$$f(x, y)=begincases
1/6 & textif 0<x<2, 0<y<6-3x \ 0 & textotherwise
&
endcases.$$



My working:
$$beginalignmathsf E(Xmid Y=5)~&=~displaystyleint_0^2 x fracfrac16f(y),mathsf d xendalign$$
where
$$beginalignmathsf f(y)~&=~displaystyleint_0^frac-y+63 frac16 ,mathsf d x = frac6-y18endalign$$



Therefore,
$$beginalignmathsf E(Xmid Y=5)~&=~displaystyleint_0^2 x fracfrac16frac6-y18,mathsf d x mathsf ~&=~displaystyleint_0^2 x fracfrac16frac6-518,mathsf d x~&=~displaystyleint_0^2 3x ,mathsf d x endalign = 6$$



But then when I compute Var(X|Y=5), the answer is getting negative, which is impossible. So I think that I might have done something wrong when calculating the expectation.



My working for Variance:
$$Var(X|Y=5) = E(X^2|Y=5) - (E(X|Y=5) )^2 = 8 - 6^2 = -28$$



I appreciate any help.







self-study pdf joint-distribution conditional-expectation






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edited 1 hour ago









Ferdi

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asked 1 hour ago









vic12

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  • you forgot the constraint on the support of $X$ given $Y=y.$
    – Xi'an
    33 mins ago
















  • you forgot the constraint on the support of $X$ given $Y=y.$
    – Xi'an
    33 mins ago















you forgot the constraint on the support of $X$ given $Y=y.$
– Xi'an
33 mins ago




you forgot the constraint on the support of $X$ given $Y=y.$
– Xi'an
33 mins ago










1 Answer
1






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oldest

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up vote
3
down vote



accepted










Think about this geometrically: we've got $(X,Y)$ uniformly distributed over the right triangle with vertices at $(0,0)$, $(2,0)$, and $(0,6)$.



If we imagine sampling over and over from this region uniformly, we can picture $E(X|Y=5)$ as the average $x$ coordinate of the points that end up on the horizontal line $y=5$. All of these points will necessarily have $0 < x < 1/3$, since if $x geq 1/3$ then $y = 5$ can't happen, and since the points are uniform over this line, this image suggests $E(X|Y=5) stackrel ?= 1/6$ (this is the midpoint of the range of $x$ points that can end up on this line).



Checking this with calculus, the issue with what you did is the limits of integration for $x$ also depend on $y$. If $y = 5$ is observed then the biggest that $x$ can be is $1/3$, so really
$$
E(X|Y=5) = int_0^1/3x frac36-y,text dx = 3 cdot frac 12 x^2bigg|_x=0^x=1/3 = frac 16.
$$




Another quick sanity check is that $E(X|Y)$ has to be within the range of $X$, so $E(X|Y=5)neq 6$ can be recognized as incorrect before the negative variance shows up.






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    1 Answer
    1






    active

    oldest

    votes








    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes








    up vote
    3
    down vote



    accepted










    Think about this geometrically: we've got $(X,Y)$ uniformly distributed over the right triangle with vertices at $(0,0)$, $(2,0)$, and $(0,6)$.



    If we imagine sampling over and over from this region uniformly, we can picture $E(X|Y=5)$ as the average $x$ coordinate of the points that end up on the horizontal line $y=5$. All of these points will necessarily have $0 < x < 1/3$, since if $x geq 1/3$ then $y = 5$ can't happen, and since the points are uniform over this line, this image suggests $E(X|Y=5) stackrel ?= 1/6$ (this is the midpoint of the range of $x$ points that can end up on this line).



    Checking this with calculus, the issue with what you did is the limits of integration for $x$ also depend on $y$. If $y = 5$ is observed then the biggest that $x$ can be is $1/3$, so really
    $$
    E(X|Y=5) = int_0^1/3x frac36-y,text dx = 3 cdot frac 12 x^2bigg|_x=0^x=1/3 = frac 16.
    $$




    Another quick sanity check is that $E(X|Y)$ has to be within the range of $X$, so $E(X|Y=5)neq 6$ can be recognized as incorrect before the negative variance shows up.






    share|cite|improve this answer


























      up vote
      3
      down vote



      accepted










      Think about this geometrically: we've got $(X,Y)$ uniformly distributed over the right triangle with vertices at $(0,0)$, $(2,0)$, and $(0,6)$.



      If we imagine sampling over and over from this region uniformly, we can picture $E(X|Y=5)$ as the average $x$ coordinate of the points that end up on the horizontal line $y=5$. All of these points will necessarily have $0 < x < 1/3$, since if $x geq 1/3$ then $y = 5$ can't happen, and since the points are uniform over this line, this image suggests $E(X|Y=5) stackrel ?= 1/6$ (this is the midpoint of the range of $x$ points that can end up on this line).



      Checking this with calculus, the issue with what you did is the limits of integration for $x$ also depend on $y$. If $y = 5$ is observed then the biggest that $x$ can be is $1/3$, so really
      $$
      E(X|Y=5) = int_0^1/3x frac36-y,text dx = 3 cdot frac 12 x^2bigg|_x=0^x=1/3 = frac 16.
      $$




      Another quick sanity check is that $E(X|Y)$ has to be within the range of $X$, so $E(X|Y=5)neq 6$ can be recognized as incorrect before the negative variance shows up.






      share|cite|improve this answer
























        up vote
        3
        down vote



        accepted







        up vote
        3
        down vote



        accepted






        Think about this geometrically: we've got $(X,Y)$ uniformly distributed over the right triangle with vertices at $(0,0)$, $(2,0)$, and $(0,6)$.



        If we imagine sampling over and over from this region uniformly, we can picture $E(X|Y=5)$ as the average $x$ coordinate of the points that end up on the horizontal line $y=5$. All of these points will necessarily have $0 < x < 1/3$, since if $x geq 1/3$ then $y = 5$ can't happen, and since the points are uniform over this line, this image suggests $E(X|Y=5) stackrel ?= 1/6$ (this is the midpoint of the range of $x$ points that can end up on this line).



        Checking this with calculus, the issue with what you did is the limits of integration for $x$ also depend on $y$. If $y = 5$ is observed then the biggest that $x$ can be is $1/3$, so really
        $$
        E(X|Y=5) = int_0^1/3x frac36-y,text dx = 3 cdot frac 12 x^2bigg|_x=0^x=1/3 = frac 16.
        $$




        Another quick sanity check is that $E(X|Y)$ has to be within the range of $X$, so $E(X|Y=5)neq 6$ can be recognized as incorrect before the negative variance shows up.






        share|cite|improve this answer














        Think about this geometrically: we've got $(X,Y)$ uniformly distributed over the right triangle with vertices at $(0,0)$, $(2,0)$, and $(0,6)$.



        If we imagine sampling over and over from this region uniformly, we can picture $E(X|Y=5)$ as the average $x$ coordinate of the points that end up on the horizontal line $y=5$. All of these points will necessarily have $0 < x < 1/3$, since if $x geq 1/3$ then $y = 5$ can't happen, and since the points are uniform over this line, this image suggests $E(X|Y=5) stackrel ?= 1/6$ (this is the midpoint of the range of $x$ points that can end up on this line).



        Checking this with calculus, the issue with what you did is the limits of integration for $x$ also depend on $y$. If $y = 5$ is observed then the biggest that $x$ can be is $1/3$, so really
        $$
        E(X|Y=5) = int_0^1/3x frac36-y,text dx = 3 cdot frac 12 x^2bigg|_x=0^x=1/3 = frac 16.
        $$




        Another quick sanity check is that $E(X|Y)$ has to be within the range of $X$, so $E(X|Y=5)neq 6$ can be recognized as incorrect before the negative variance shows up.







        share|cite|improve this answer














        share|cite|improve this answer



        share|cite|improve this answer








        edited 1 hour ago

























        answered 1 hour ago









        jld

        11.5k23149




        11.5k23149



























             

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