If we have a random variable and any number , what is the probability that ? If we know the mean of , Markov’s inequality can give an upper bound on the probability that . As it turns out, this upper bound is rather loose, and it can be improved if we know the variance of in addition to its mean. This result is known as Chebyshev’s inequality after the name of the famous mathematician Pafnuty Lvovich Chebyshev. It was first proved by his student Andrey Markov who provided a proof in 1884 in his PhD thesis (see wikipedia).

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