(Easy?) Probability Q: Uniform in Uniform

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Homework Help Overview

The discussion revolves around a probability problem involving uniformly distributed random variables. The original poster seeks to find the expectation of the length of a chosen subinterval based on the values of two independent uniform random variables, X and Y, both defined on the interval [0, 1].

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the setup of the problem, particularly the definition of the length L based on the values of Y relative to X. There are attempts to compute the expectation using double integrals, but discrepancies in results prompt questions about the formulation of these integrals.

Discussion Status

Some participants have pointed out potential errors in the integrals used for calculating the expectation. There is an acknowledgment of the need to clarify the value functions and densities involved in the expectation calculations. The conversation reflects a mix of attempts to correct misunderstandings and explore the problem further.

Contextual Notes

One participant mentions being new to the topic and seeks guidance on a different uniform probability distribution question, indicating a broader context of learning and inquiry within the thread.

ryzeg
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Hello

I have been struggling with a simple probability question.

Homework Statement



We are given that X is a uniformly distributed random variable on [0, 1]. After X is chosen, we take another uniform [0, 1] random variable Y (independent of X) and choose the subinterval that Y falls in. L is the length of this chosen subinterval (either [0, X] or (X, 1]), and we want its expectation.

Homework Equations



The expectation of a uniform random variable is (a+b)/2, where a and b are the interval bounds. These equations may also be useful:

f_{Y}(y|X=x) = \frac{f(x,y)}{f_{X}(x)}

f_{X}(x|Y=y) = \frac{f_{Y}(y|X=x)f_{X}(x)}{f_{Y}(y)}

E(g(Y)|X=x) = \int \! g(y)f_{Y}(y|X=x) \,dx

E(Y) = \int \! E(Y|X=x)f_{X}(x) \,dx

The Attempt at a Solution



I notice

L=\left\{\begin{array}{cc}X,&amp;\mbox{ if }<br /> Y\leq X\\1-X, &amp; \mbox{ if } Y&gt;Z\end{array}\right

And E(X) is obviously 1/2... but I do not know how to find E(L) :(

I tried doing double integrals for expectation on both cases, and summing these, but I get 1/2 which doesn't seem right...

E_0(L) = \int_{0}^{1} \int_{0}^{x} \! 1 y \, dy \,dx = 1/3

E_1(L) = \int_{0}^{1} \int_{x}^{1} \! 1 y \, dy \,dx = 1/6

E(L) = E_0 + E_1 = 1/3 + 1/6 = 1/2

Any help?
 
Last edited:
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Where is the "y" in your expectation integrals coming from?
The value function is either f(x) = x (when y < x) or f(x) = 1 - x (when y > x). I don't see that in your integrals.

Recall that \int f(x)g(x) dx is the integral for expectation where f(x) is the value function and g(x) is the density. Make sure when you construct your integrals that you have the right values and densities.
 
I was using y as the value function, with the bounds ranging over all possible values.

When I do integrals with x*1 from 0 to 1, I still get 1/2.
 
Are these your integrals?

<br /> E_0(L) = \int_{0}^{1} \int_{0}^{x} x \, dy \,dx <br />

<br /> E_1(L) = \int_{0}^{1} \int_{x}^{1} 1 - x \, dy \,dx <br />

They don't add up to 1/2.
 
Yeah, you're right, I did my integrals wrong. By symmetry, it is obvious that it should be 2/3, which is what those add up to. Thanks!
 
hi there I am new with this stuff but need some help... I've given a question in Finding C,D, F(x). Where the mean is 10 standard deviation is 1. (Uniform Probability distribution) Can you tell me which formula i should used...
Thanks
 

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