Probability

Cumulative Distribution Function

Also known as: CDF

The probability that a random variable takes a value at or below a given point.

F(x) = P(X <= x). Non-decreasing, right-continuous, running from 0 to 1.

Why it matters in interviews. The CDF is the fast route to maxima and minima. The maximum of n independent variables is at most x exactly when all of them are, so F_max(x) = F(x)^n - one line, then differentiate if you need the density.

Minima use the complement: P(min > x) = (1 - F(x))^n.

Inverse transform sampling: if U is uniform on [0,1] then F inverse of U has distribution F. This is how random variates are generated from a uniform generator.

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