Math 2.0

statement proposition

Monotonicity of the cumulative distribution function

Statement

Let XX be a real random variable with cumulative distribution function FXF_X. Then FXF_X is nondecreasing: if x≤yx \le y, then FX(x)≤FX(y)F_X(x) \le F_X(y).

Remarks

The proof: {X≤x}⊆{X≤y}\{X \le x\} \subseteq \{X \le y\}, so the claim follows from the monotonicity of probability. More precisely, FX(y)−FX(x)=P(x<X≤y)≥0F_X(y) - F_X(x) = P(x < X \le y) \ge 0. A nondecreasing function has at most countably many points of discontinuity. So P(X=x)>0P(X = x) > 0 for at most countably many xx.

Explanations

L1 human

As xx moves to the right, the event "X≤xX \le x" contains more outcomes, so its probability cannot go down.

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Sources

  1. Web https://en.wikipedia.org/wiki/Cumulative_distribution_function, Properties