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[parent] proof of Markov's inequality (Proof)

Define $$ Y = \begin{cases} d & X \ge d \\ 0 & \text{otherwise} \\ \end{cases}. $$ Then $0 \le Y \le X$ Additionally, it follows immediately from the definition that $Y$ is a random variable (i.e., that it is measurable). Computing the expected value of $Y$ we have that $$ \mathbb{E}[X] \ge \mathbb{E}[Y] = d\cdot\mathbb{P}_{}\left\{X \ge d\right\}, $$ and the inequality follows.




"proof of Markov's inequality" is owned by Andrea Ambrosio. [ full author list (2) | owner history (1) ]
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Cross-references: inequality, expected value, measurable, random variable

This is version 4 of proof of Markov's inequality, born on 2002-06-16, modified 2006-09-11.
Object id is 3111, canonical name is ProofOfMarkovsInequality.
Accessed 92728 times total.

Classification:
AMS MSC60A99 (Probability theory and stochastic processes :: Foundations of probability theory :: Miscellaneous)

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