Probability- expected value of Z, where z= X/(1+y)^2

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Homework Help Overview

The problem involves calculating the expected value of a random variable Z, defined as Z = X/(1+Y)^2, where X and Y are independent random variables uniformly distributed between 0 and 1.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the expected value of Z and explore the relationship between the distributions of X and Y. There are attempts to express E[Z] in terms of E[X] and E[1/(1+Y)^2]. Questions arise regarding the distribution of the transformed variable (1+Y)^(-2) and whether it remains uniform after transformation.

Discussion Status

Participants are actively engaging with the problem, raising questions about the implications of transformations on distributions and exploring different approaches to calculating the expected value. Some guidance has been offered regarding the use of double integrals to compute E[Z].

Contextual Notes

There is a noted confusion about the distribution of transformed variables and the impact of adding constants to uniform random variables. Participants express uncertainty about the implications of these transformations on the expected value calculation.

Roni1985
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Homework Statement



X & Y are independent r.v.s with uniform distribution between 0 and 1.

Z= X/(1+Y)^2

find E[Z].

Homework Equations





The Attempt at a Solution



Here is what I did.

E[Z]= E[X]*E[1/(1+Y)^2]
E[X]=1/2
E[1/(1+Y)^2]=?
I think that once I know the distribution of (1+Y)^(-2), I'll be able to find the answer. Is it 1/(1+Y)^2~ U(1,2) ?
 
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You can also use this theorem:

E[g(X,Y)]=\iint{g(x,y)f_{X,Y}(x,y)dxdy}

So, in your case, this comes down to

\int_0^1\int_0^1\frac{x}{1+y^2}dxdy
 
micromass said:
You can also use this theorem:

E[g(X,Y)]=\iint{g(x,y)f_{X,Y}(x,y)dxdy}

So, in your case, this comes down to

\int_0^1\int_0^1\frac{x}{1+y^2}dxdy


Hey,

thanks for the answer.

Is 1+y^2 a typo in your answer?
so adding a constant to a uniform r.v. doesn't change it's distribution?
 
Roni1985 said:
Is 1+y^2 a typo in your answer?

Yes

so adding a constant to a uniform r.v. doesn't change it's distribution?

Obviously it does change the distribution. But I don't see how that is important here.
 
Roni1985 said:

Homework Statement



X & Y are independent r.v.s with uniform distribution between 0 and 1.

Z= X/(1+Y)^2

find E[Z].

Homework Equations





The Attempt at a Solution



Here is what I did.

E[Z]= E[X]*E[1/(1+Y)^2]
E[X]=1/2
E[1/(1+Y)^2]=?
I think that once I know the distribution of (1+Y)^(-2), I'll be able to find the answer. Is it 1/(1+Y)^2~ U(1,2) ?

If W = 1/(1+Y)^2, then for any w > 0 we have P{W <= w} = P{1/(1+Y)^2 <= w} = P{-sqrt(w) <= 1/(1+Y) <= sqrt(w)}. The left-hand inequality -sqrt(w) <= 1/(1+Y) holds automatically because Y >= 0, so P{W <= w} = P{1/(1+Y) <= sqrt(w)} = P{Y >= -1 + 1/sqrt(w)}. Since Y ~ U(0,1), we can easily get P{W <= w} and hence can get the density function of W. Alternatively: just apply the standard formula for the density of a transformed random variable.

RGV
 
micromass said:
Obviously it does change the distribution. But I don't see how that is important here.
Well I was thinking that now its uniformly distributed from 1 to 2... isn't it?

EDIT:
Oh right its still uniform from 0 to 1...
omg... I'm so rusty :\

Thanks.
 
Last edited:
Roni1985 said:
Well I was thinking that now its uniformly distributed from 1 to 2... isn't it?

EDIT:
Oh right its still uniform from 0 to 1...
omg... I'm so rusty :\

Thanks.

You have all the information you need to work out the answer for yourself.

RGV
 

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