Compute $Var(X)$ with Gamma distribution
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$$f_X, Y (x, y) =begincases
24xy & x geq 0, ygeq0, x+y leq 1\
0 & textotherwise \
endcases
$$
Compute $Var(X)$.
This question was done with a shortcut:
$f_X(x) = int_0^1-x24xydy = 12x(1-x)^2, 0 leq x leq 1$ and zero otherwise.
Recall that this is $beta(a = 2, b = 3)$, and that $V(X) = fracab(a+b)^2(a+b+1)$. So.
$V(X) = frac2 cdot 3(2 + 3)^2(2+3+1) = 0.04$.
My question is how did they get the interval $0 leq x leq 1$? $x geq 0$ and $x leq 1 - y$. :/
probability variance
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1
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$$f_X, Y (x, y) =begincases
24xy & x geq 0, ygeq0, x+y leq 1\
0 & textotherwise \
endcases
$$
Compute $Var(X)$.
This question was done with a shortcut:
$f_X(x) = int_0^1-x24xydy = 12x(1-x)^2, 0 leq x leq 1$ and zero otherwise.
Recall that this is $beta(a = 2, b = 3)$, and that $V(X) = fracab(a+b)^2(a+b+1)$. So.
$V(X) = frac2 cdot 3(2 + 3)^2(2+3+1) = 0.04$.
My question is how did they get the interval $0 leq x leq 1$? $x geq 0$ and $x leq 1 - y$. :/
probability variance
2
The intervals are specified explicitly in the definition of the function (your first line).
â David G. Stork
Aug 10 at 23:51
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up vote
1
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up vote
1
down vote
favorite
$$f_X, Y (x, y) =begincases
24xy & x geq 0, ygeq0, x+y leq 1\
0 & textotherwise \
endcases
$$
Compute $Var(X)$.
This question was done with a shortcut:
$f_X(x) = int_0^1-x24xydy = 12x(1-x)^2, 0 leq x leq 1$ and zero otherwise.
Recall that this is $beta(a = 2, b = 3)$, and that $V(X) = fracab(a+b)^2(a+b+1)$. So.
$V(X) = frac2 cdot 3(2 + 3)^2(2+3+1) = 0.04$.
My question is how did they get the interval $0 leq x leq 1$? $x geq 0$ and $x leq 1 - y$. :/
probability variance
$$f_X, Y (x, y) =begincases
24xy & x geq 0, ygeq0, x+y leq 1\
0 & textotherwise \
endcases
$$
Compute $Var(X)$.
This question was done with a shortcut:
$f_X(x) = int_0^1-x24xydy = 12x(1-x)^2, 0 leq x leq 1$ and zero otherwise.
Recall that this is $beta(a = 2, b = 3)$, and that $V(X) = fracab(a+b)^2(a+b+1)$. So.
$V(X) = frac2 cdot 3(2 + 3)^2(2+3+1) = 0.04$.
My question is how did they get the interval $0 leq x leq 1$? $x geq 0$ and $x leq 1 - y$. :/
probability variance
edited Aug 11 at 0:41
asked Aug 10 at 23:32
Bas bas
39611
39611
2
The intervals are specified explicitly in the definition of the function (your first line).
â David G. Stork
Aug 10 at 23:51
add a comment |Â
2
The intervals are specified explicitly in the definition of the function (your first line).
â David G. Stork
Aug 10 at 23:51
2
2
The intervals are specified explicitly in the definition of the function (your first line).
â David G. Stork
Aug 10 at 23:51
The intervals are specified explicitly in the definition of the function (your first line).
â David G. Stork
Aug 10 at 23:51
add a comment |Â
2 Answers
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Well, let's take a look how the conditions look on (x,y) plane
The blue line is the equation $x+y=1$. Now since we are interested in the positive quadrant $x>0$ and $y>0$, I only drew that part. So the area surface where your function $f(x,y)$ is non-zero is within the triangle where $x$ moves along the red arrow and $y$ moves along the black one.
Notice that $0 < x < 1$ and since $y$ is below the line then $x+y<1$ or $y<1-x$.
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Here is the distribution:
Here is $f_X(x) = 12 x (1 - x)^2$:
The mean is shown in red and $pm sigma$ in purple.
The mean is $intlimits_x=0^1 x f_X(x) dx = 2 over 5$.
The variance is:
$intlimits_x=0^1 (x - mu)^2 f_X(x) dx = 1 over 25 = 0.04$ (as you calculated).
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
Well, let's take a look how the conditions look on (x,y) plane
The blue line is the equation $x+y=1$. Now since we are interested in the positive quadrant $x>0$ and $y>0$, I only drew that part. So the area surface where your function $f(x,y)$ is non-zero is within the triangle where $x$ moves along the red arrow and $y$ moves along the black one.
Notice that $0 < x < 1$ and since $y$ is below the line then $x+y<1$ or $y<1-x$.
add a comment |Â
up vote
1
down vote
Well, let's take a look how the conditions look on (x,y) plane
The blue line is the equation $x+y=1$. Now since we are interested in the positive quadrant $x>0$ and $y>0$, I only drew that part. So the area surface where your function $f(x,y)$ is non-zero is within the triangle where $x$ moves along the red arrow and $y$ moves along the black one.
Notice that $0 < x < 1$ and since $y$ is below the line then $x+y<1$ or $y<1-x$.
add a comment |Â
up vote
1
down vote
up vote
1
down vote
Well, let's take a look how the conditions look on (x,y) plane
The blue line is the equation $x+y=1$. Now since we are interested in the positive quadrant $x>0$ and $y>0$, I only drew that part. So the area surface where your function $f(x,y)$ is non-zero is within the triangle where $x$ moves along the red arrow and $y$ moves along the black one.
Notice that $0 < x < 1$ and since $y$ is below the line then $x+y<1$ or $y<1-x$.
Well, let's take a look how the conditions look on (x,y) plane
The blue line is the equation $x+y=1$. Now since we are interested in the positive quadrant $x>0$ and $y>0$, I only drew that part. So the area surface where your function $f(x,y)$ is non-zero is within the triangle where $x$ moves along the red arrow and $y$ moves along the black one.
Notice that $0 < x < 1$ and since $y$ is below the line then $x+y<1$ or $y<1-x$.
answered Aug 11 at 0:56
Ahmad Bazzi
3,0601419
3,0601419
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add a comment |Â
up vote
0
down vote
Here is the distribution:
Here is $f_X(x) = 12 x (1 - x)^2$:
The mean is shown in red and $pm sigma$ in purple.
The mean is $intlimits_x=0^1 x f_X(x) dx = 2 over 5$.
The variance is:
$intlimits_x=0^1 (x - mu)^2 f_X(x) dx = 1 over 25 = 0.04$ (as you calculated).
add a comment |Â
up vote
0
down vote
Here is the distribution:
Here is $f_X(x) = 12 x (1 - x)^2$:
The mean is shown in red and $pm sigma$ in purple.
The mean is $intlimits_x=0^1 x f_X(x) dx = 2 over 5$.
The variance is:
$intlimits_x=0^1 (x - mu)^2 f_X(x) dx = 1 over 25 = 0.04$ (as you calculated).
add a comment |Â
up vote
0
down vote
up vote
0
down vote
Here is the distribution:
Here is $f_X(x) = 12 x (1 - x)^2$:
The mean is shown in red and $pm sigma$ in purple.
The mean is $intlimits_x=0^1 x f_X(x) dx = 2 over 5$.
The variance is:
$intlimits_x=0^1 (x - mu)^2 f_X(x) dx = 1 over 25 = 0.04$ (as you calculated).
Here is the distribution:
Here is $f_X(x) = 12 x (1 - x)^2$:
The mean is shown in red and $pm sigma$ in purple.
The mean is $intlimits_x=0^1 x f_X(x) dx = 2 over 5$.
The variance is:
$intlimits_x=0^1 (x - mu)^2 f_X(x) dx = 1 over 25 = 0.04$ (as you calculated).
edited Aug 11 at 0:52
answered Aug 11 at 0:39
David G. Stork
7,8912930
7,8912930
add a comment |Â
add a comment |Â
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2
The intervals are specified explicitly in the definition of the function (your first line).
â David G. Stork
Aug 10 at 23:51