Applied Probability Calculation not Working Out (Integrals)

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SUMMARY

The discussion focuses on the calculation of the conditional expectation E[X | Y = y] using the joint density function f(x,y) = (e^(-x/y)e^(-y))/y for X and Y, where both variables range from 0 to infinity. The user encounters difficulties in deriving the conditional density fX|Y(x|y) and expresses confusion regarding the integration limits for fY(y). The correct integral for fY(y) is established as ∫_0^∞ (1/y)e^(-x/y) dx = y, leading to the conclusion that E[X | Y = y] = y is valid.

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jumbogala
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Homework Statement


The joint density of X and Y is given by
f(x,y) = [e-x/y)e-y ] / y

x is between 0 and infinity; y is between 0 and infinity

Show E[X |Y = y] = y.

Jump to the last part of this post in bold if you just want to check my calculus calculations and skip the probability stuff.

Homework Equations


The Attempt at a Solution


First I need to find fX|Y (x|y). To do this I need to take f(x,y) and divide by fY(y).

I think it's the latter which is messing me up. My understanding is that to find it, I need to integrate f(x,y) with respect to x.

The solutions manual does that, but there are no limits on their integral. Shouldn't the limits be from 0 to infinity?

They have [(1/y)e-x/ye-y ] / [e-y ∫ (1/y)e(-x/y) dx ] = (1/y)e-x/y

Which in my calculations doesn't work out! I get -1/y. What am I doing wrong?
 
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jumbogala said:
The solutions manual does that, but there are no limits on their integral. Shouldn't the limits be from 0 to infinity?

They have [(1/y)e-x/ye-y ] / [e-y ∫ (1/y)e(-x/y) dx ] = (1/y)e-x/y

Which in my calculations doesn't work out! I get -1/y. What am I doing wrong?

The integral is

[tex]\int_0^\infty e^{-x/y} dx = -y ( 0 - 1 ) = y.[/tex]
 

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