Markov's inequality is a result in probability theory that provides an upper bound on the probability that a non-negative random variable is greater than or equal to a positive constant. The inequality is named after the Russian mathematician Andrey Markov. The statement of Markov's inequality is as follows: Let \(X\) be a non-negative random variable (i.e., \(X \geq 0\)), and let \(a > 0\) be a positive constant.
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