In probability theory, Hoeffding's inequality provides an upper bound on the probability that the sum of bounded independent random variables deviates from its expected value by more than a certain amount. Hoeffding's inequality was proven by Wassily Hoeffding in 1963. Hoeffding's inequality is a special case of the Azuma–Hoeffding inequality and McDiarmid's inequality. It is similar to the Chernoff bound, but tends to be less sharp, in particular when the variance of the random variables is small. It is similar to, but incomparable with, one of Bernstein's inequalities.
Statement Let X1, ..., Xn be independent random variables such that a i ≤ X i ≤ b i {\displaystyle a_{i}\leq X_{i}\leq b_{i}} almost surely. Consider the sum of these random variables,
S n = X 1 + ⋯ + X n . {\displaystyle S_{n}=X_{1}+\cdots +X_{n}.}
Then Hoeffding's theorem states that, for all t > 0,
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