Conditional probability with marginal and joint density

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Homework Help Overview

The discussion revolves around determining the conditional probability ##P(X0)## involving random variables X and Y with a specified joint density function. The problem includes marginal densities and requires understanding the boundaries for integration in the context of conditional probability.

Discussion Character

  • Exploratory, Assumption checking, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the application of the conditional probability formula and express uncertainty about the appropriate boundaries for the joint density function. There are attempts to visualize the problem using graphical representations of the relevant inequalities.

Discussion Status

Some participants have provided guidance on visualizing the problem and suggested limits for integration. There is ongoing exploration of the marginal density function, with some questioning its validity over certain ranges. Multiple interpretations of the problem setup are being considered.

Contextual Notes

Participants note potential issues with the marginal density function, particularly regarding its behavior for negative values of x. There is a recognition of the need for clarity in the definitions and boundaries used in the calculations.

Linder88
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Homework Statement


Determine ##P(X<Y|x>0)##

Homework Equations


X and Y are random variables with the joint density function
$$
f_{XY}(x,y)=
\begin{cases}
4|xy|,-y<x<y,0<y<1\\
0,elsewhere
\end{cases}$$
The marginal densities are given by
$$
f_X(x)=2x\\
f_Y(y)=4y^3
$$

The Attempt at a Solution


The formula for conditional probability is
$$
P(B|A)=\frac{P(B\cap A)}{P(A)}
$$
In this case we have
$$
P(X<Y|x>0)=\frac{P(X<Y\cap x>0)}{P(x>0)}=\frac{F_{XY}(x,y)}{F_X(x)}=\frac{\int_{}4|xy|dxdy}{\int_0^{\infty}2xdx}
$$
This is where I get stuck, I do not know what boundaries I should put for the joint density function, can someone please help me?
 
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Linder88 said:

Homework Statement


Determine ##P(X<Y|x>0)##

Homework Equations


X and Y are random variables with the joint density function
$$
f_{XY}(x,y)=
\begin{cases}
4|xy|,-y<x<y,0<y<1\\
0,elsewhere
\end{cases}$$
The marginal densities are given by
$$
f_X(x)=2x\\
f_Y(y)=4y^3
$$

The Attempt at a Solution


The formula for conditional probability is
$$
P(B|A)=\frac{P(B\cap A)}{P(A)}
$$
In this case we have
$$
P(X<Y|x>0)=\frac{P(X<Y\cap x>0)}{P(x>0)}=\frac{F_{XY}(x,y)}{F_X(x)}=\frac{\int_{}4|xy|dxdy}{\int_0^{\infty}2xdx}
$$
This is where I get stuck, I do not know what boundaries I should put for the joint density function, can someone please help me?

Draw the lines ##x=y##, ##x=-y##, ##y=0##, and ##y=1##. Shade the part where x and y are between the appropriate lines. The limits are just like in any double integral in calculus. Also, I didn't check your work but surely if the marginal density is ##2x##, it wouldn't be valid clear to ##\infty##.
 
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Linder88 said:

Homework Statement


Determine ##P(X<Y|x>0)##

Homework Equations


X and Y are random variables with the joint density function
$$
f_{XY}(x,y)=
\begin{cases}
4|xy|,-y<x<y,0<y<1\\
0,elsewhere
\end{cases}$$
The marginal densities are given by
$$
f_X(x)=2x\\
f_Y(y)=4y^3
$$

The Attempt at a Solution


The formula for conditional probability is
$$
P(B|A)=\frac{P(B\cap A)}{P(A)}
$$
In this case we have
$$
P(X<Y|x>0)=\frac{P(X<Y\cap x>0)}{P(x>0)}=\frac{F_{XY}(x,y)}{F_X(x)}=\frac{\int_{}4|xy|dxdy}{\int_0^{\infty}2xdx}
$$
This is where I get stuck, I do not know what boundaries I should put for the joint density function, can someone please help me?

You claimed ##f_X(x) = 2x## cannot possibly be correct. In the sample space, ##x## is allowed to be both ##< 0## and ##>0##, and when ##x < 0## your formula delivers a negative probability.
 
LCKurtz said:
Draw the lines ##x=y##, ##x=-y##, ##y=0##, and ##y=1##. Shade the part where x and y are between the appropriate lines. The limits are just like in any double integral in calculus. Also, I didn't check your work but surely if the marginal density is ##2x##, it wouldn't be valid clear to ##\infty##.
The shaded area is a inverted triangle in the upper half of the plane with y vertical and x horizontal, so we have that
$$
P(X<Y|x>0)=\frac{\int_0^1\int_{-y}^y4|xy|dxdy}{\int_0^12xdx}=\frac{1}{1}=1
$$
I guess this concludes this topic, thanks :)
 
Linder88 said:
The shaded area is a inverted triangle in the upper half of the plane with y vertical and x horizontal, so we have that
$$
P(X<Y|x>0)=\frac{\int_0^1\int_{-y}^y4|xy|dxdy}{\int_0^12xdx}=\frac{1}{1}=1
$$
I guess this concludes this topic, thanks :)

For the record: your final answer is correct, but you have computed ##f_X(x)## incorrectly. You should have gotten
f_X(x) = \frac{1}{2} |x| ( 1 - x^2),\; 0 \leq x \leq 1
Unlike your answer, this has ##f_X > 0## for both ##-1 < x < 0## and ##0 < x < 1##.
 
Ray Vickson said:
For the record: your final answer is correct, but you have computed ##f_X(x)## incorrectly. You should have gotten
f_X(x) = \frac{1}{2} |x| ( 1 - x^2),\; 0 \leq x \leq 1
Unlike your answer, this has ##f_X > 0## for both ##-1 < x < 0## and ##0 < x < 1##.

Did you mean $$2*|x| ( 1 - x^2),\; 0 \leq x \leq 1\text{ ?}$$
 
LCKurtz said:
Did you mean $$2*|x| ( 1 - x^2),\; 0 \leq x \leq 1\text{ ?}$$

Yes. I accidentally omitted the factor '4' in front, so got 1/2 instead of 4/2 = 2.
 

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