Statement
If X is any random variable and a > 0, then
In the language of measure theory, Markov's inequality states that if (X, Σ, μ) is a measure space, ƒ is a measurable extended real-valued function, and, then
(This measure theoretic definition may sometimes be referred to as Chebyshev's inequality .)
Read more about this topic: Markov's Inequality
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—Ralph Waldo Emerson (1803–1882)