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Cumulative distribution function. While the PDF gives the probability density of each value of a random variable, the CDF (often denoted $F(x)$) gives the probability that the random variable will be less than or equal to a specified value.

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If $X=\sin\Theta$ and $Y=\cos\Theta$ with $\Theta$ uniformly distributed, how can I compute ...

$\Theta \sim U(-\pi, \pi)$ so the density of $\Theta$ is given by $\frac{1}{2 \pi}$ in $-\pi, \pi$. $F(x, y) = P(X \le x, Y \le y) = P(\Theta \le \arcsin(x) \wedge \arccos(y))$. $ F(x, y) = \frac{1 …
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Why is the CDF of a sample uniformly distributed

Assume $F_X$ is continuous and increasing. Define $Z = F_X(X)$ and note that $Z$ takes values in $[0, 1]$. Then $$F_Z(x) = P(F_X(X) \leq x) = P(X \leq F_X^{-1}(x)) = F_X(F_X^{-1}(x)) = x.$$ The deriva …
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