How to Find the PDF for a Uniform Distribution on a Disc?

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Homework Help Overview

The discussion revolves around finding the probability density function (PDF) for a uniform distribution on a disc defined by the equation \(x^2 + y^2 \leq 1\). Participants are exploring the characteristics of uniform distributions in two dimensions.

Discussion Character

  • Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the formulation of the PDF, with one suggesting a formula that appears non-uniform, while another proposes a corrected version. There are inquiries about integrating the PDF to verify normalization and questions regarding the limits for finding marginal distributions.

Discussion Status

The conversation is ongoing, with participants providing different formulations of the PDF and questioning the validity of these approaches. There is no explicit consensus yet, but some guidance is being offered regarding the correct form of the PDF and integration challenges.

Contextual Notes

One participant mentions attempting to integrate the PDF to confirm that it sums to one, indicating potential confusion about the limits of integration and the process for marginal distributions.

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Homework Statement



[tex]\D = \{(x,y) \in \mathbb{R}^2 | x^2 + y^2 \leq 1\}[/tex] i.e. a disc or radius 1.
Write down the pdf f_{xy} for a uniform distribution on the disc.

Homework Equations





The Attempt at a Solution



[tex]f_{xy} = \frac{(x^2 + y^2)}{\pi} \mbox{for} x^2 + y^2 \leq 1[/tex] 0 otherwise
as the area of the disc pi and to make it uniform you divide by pi so the probability integrates to 1
 
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Hmmm...

[tex]f_{xy} = \frac{(x^2 + y^2)}{\pi}[/tex]

Doesn't look very uniform to me:wink:
 
i think i got it: its [tex] f(x,y)_{xy} = \left\{ \begin{array}{rl}<br /> \frac{1}{\pi} &\mbox{for } x^2 + y^2 \leq 1\\<br /> 0 &\mbox{otherwise}[/tex]

thanks
 
Last edited:
Looks good to me!:approve:
 
I am doing a some practice questions for stats and i tried to integrate this to get 1 but i can't so what are the appropriate limits and how would i go about finding the marginal distribution of x and y? Thanks
 

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