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Let X be any real-valued random variable such that almost surely, i.e. with probability one. Then, for all ,
or equivalently,
Proof
The following proof is direct but somewhat ad-hoc. Another proof uses exponential tilting;[2]: Lemma 2.2 proofs with a slightly worse constant are also available using symmetrization.[3]
Without loss of generality, by replacing by , we can assume , so that .
Since is a convex function of , we have that for all ,
So,
where . By computing derivatives, we find
and .
From the AMGM inequality we thus see that for all , and thus, from Taylor's theorem, there is some such that
^Boucheron, Stéphane; Lugosi, Gábor; Massart, Pascal (2013). Concentration Inequalities: A Nonasymptotic Theory of Independence. Oxford University Press.