For a positive continuous random variable X, write down the PDF of Y = X² in terms of the PDF of X
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Originally Posted by ulysses123 For a positive continuous random variable X, write down the PDF of Y = X² in terms of the PDF of X Let the CDF of $\displaystyle X$ be $\displaystyle F(x) $and that of $\displaystyle Y$ be $\displaystyle G(y)$. Then: $\displaystyle G(y)=P(Y>y)=P(Y>x^2)=P(X>\sqrt{y})=F(\sqrt{y})$ and now differentiate wrt $\displaystyle y$. CB
the cdf gives the probability P(X<x) for some x , why do you have a greater than sighn?
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