Expectation and Variance for Continous Uniform RV

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Homework Help Overview

The problem involves independent continuous random variables X and Y, each uniformly distributed on the interval [0,1]. Participants are tasked with finding the mean and variance of the sum X+Y, as well as calculating and graphing the probability density function (pdf) for X+Y using convolution.

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Some participants attempt to calculate the mean and variance directly from the pdfs, while others explore the convolution method for deriving the pdf of X+Y. There are questions about the limits of integration and the correctness of the density function used.

Discussion Status

Participants are sharing their calculations and results, with some expressing uncertainty about their answers. There is a recognition of discrepancies in results, particularly regarding the mean and variance. Suggestions have been made to verify calculations and consider the implications of the uniform distribution's support.

Contextual Notes

Some participants note the importance of considering the range of values for X+Y, which can vary from 0 to 2, and the need to ensure that the pdf integrates to 1 over this range. There are indications of confusion regarding the application of the convolution formula and the setup of the problem.

darkestar
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Homework Statement



8. Suppose that X and Y are independent continuous random variables, and each is uniformly distributed on the interval [0,1] (thus the pdfs for X and Y are zero outside of this interval and equal to one on [0,1]).

(a) Find the mean and variance for X+Y.

(b) Calculate and graph the pdf for X+Y (using the convolution formula, and be careful to remember that the pdf of X vanishes outside of [0,1], etc).

Homework Equations



fX+Y = fX * fY

X + Y = Z


The Attempt at a Solution



I know that the density functions for X and Y are both 1 since the continuous distribution is 1/(b-a). To get the density function for Z, I calculated [tex]\int[/tex] fX(x) * fY(z-x) dx from 0 to z. Since this simplifies to [tex]\int[/tex] 1 dx from 0 to z. I get fZ(z) = z.

Using the density function of Z, I calculate the mean, which is E(Z = z) = [tex]\int[/tex] z2 dz from 0 to 1. I get 1/3 for my mean when I evaluate the integral.

To get the second moment, i.e. E(Z2) : [tex]\int[/tex] z3 dz from 0 to 1. When I evaluate this I get 1/4. To get the variance I then get E(Z2) - E(Z)2 which is 1/4 - 1/9 = 5/36.

I don't know if this is right though.
 
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Remember that X and Y take on values between 0 and 1. So X+Y can take on values between 0 and 2. Draw some lines for z = x+y = various constants on your square. If you calculate [itex]P(Z\le z)[/itex] directly from your uniform distribution on the square, you will probably see what the instructors caveat about the densities being 0 off the square has to do with it.
 
I calculated the mean of X+Y to be 1. The variance resulted in 1/6. I am not getting the same answer when I use the density function for Z that I tried calculating. Even when I use the limits from 0 to 2, I get a different mean and variance is negative which tells me I am wrong somewhere.

I'm quite sure I did part a correctly, but I am still struggling with part b.
 
darkestar said:
I calculated the mean of X+Y to be 1. The variance resulted in 1/6. I am not getting the same answer when I use the density function for Z that I tried calculating. Even when I use the limits from 0 to 2, I get a different mean and variance is negative which tells me I am wrong somewhere.

I'm quite sure I did part a correctly, but I am still struggling with part b.

No, you don't have part a correct. Just check it:

[tex]\hbox{Does }\int_0^2 f_Z(z) dz = 1\hbox{ ?}[/tex]

If you show your calculations it might be possible to point out your mistake. If you are using the convolution formulas, are you starting something like this, using the convolution formula:

[tex]f_Z(z) = \int_{-\infty}^{\infty}f_X(x)f_Y(z-x)dx = \int_{0}^{1}1\cdot f_Y(z-x)dx[/tex]

If so, you need to take care about where the values of z lie and the value of fY
 
Here is my work for part a. I got the answer without finding the pdf for X+Y. When I tried using pdf for X+Y which I called Z, the answers weren't matching. [PLAIN]http://img338.imageshack.us/img338/1226/partaprob.jpg
 
Last edited by a moderator:
darkestar said:
Here is my work for part a. I got the answer without finding the pdf for X+Y. When I tried using pdf for X+Y which I called Z, the answers weren't matching.

That is because you haven't calculated the pdf of X+Y correctly. I have given you two different suggestions how to do that.
 

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