Finding the PDF of Y = X2 with Given E(X) and E(X2)

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Homework Help Overview

The problem involves finding the probability density function (pdf) of the random variable Y, defined as Y = X², given the pdf of X and its expected values E(X) and E(X²). The context is within probability theory and random variables.

Discussion Character

  • Exploratory, Conceptual clarification, Problem interpretation

Approaches and Questions Raised

  • Participants discuss methods for determining the pdf of Y, with some suggesting the use of cumulative distribution functions (CDFs) and others questioning the necessity of finding the CDF of X first. There is also a focus on understanding the relationship between the variables and the intervals involved.

Discussion Status

The discussion is active, with participants exploring different methods and clarifying concepts related to the problem. Some guidance has been offered regarding the use of CDFs and the relationship between Y and X, but no consensus has been reached on a specific approach.

Contextual Notes

Participants are working with the constraints of the given pdf of X and its expected values, which may influence their approaches to finding the pdf of Y. There is an emphasis on understanding the intervals corresponding to the transformation from X to Y.

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Homework Statement


random variable of X has pdf: f(x) = (3/16)*x2 from interval (-2,2). Also, E(X) = 0, and E(X2) = 12/5. Find the pdf of Y = X2


Homework Equations





The Attempt at a Solution


I don't really know where to start.
 
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There are a couple of methods to do this. One of the easiest to understand conceptually is to calculate the probability that Y is less than or equal to some y in terms of X.

P(Y≤y) = P(X2≤y) = ...

Now P(Y≤y) is just FY(y), the cdf of Y, so to find fY(y), the pdf of Y, just differentiate it.
 
so first I should find the cdf of X by integrating the pdf of X, then I should find the cdf of Y, and then differentiate that to get the pdf of Y? How do I get the cdf of Y from the cdf of X^2?
 
You don't need to find the cdf of X first, though you certainly can use it to solve the problem. I think you should first determine what interval [a,b] of X corresponds to the condition X2≤y. Then you use P(X2≤y) = P(a≤X≤b). This second probability you can calculate using the cdf of X if you found that or you can find it using fX(x), whichever you prefer.
 

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