Hoeffding's Inequality gives an upper bound on the probability that the sum of independent, bounded random variables deviates from its expected value by more than a given amount, with the bound shrinking exponentially as the deviation grows. Named for Wassily Hoeffding, it is a foundational concentration-of-measure result used throughout probability, statistics and theoretical computer science to control the tail behavior of sums of bounded random quantities.
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StatementIn 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. 2 Classification
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Entity-backed identity for the statement-form enum value this theorem already carries, resolved to a mathematics concept by an explicit value-to-entity map (phase 3 bucket conversion, docs\design_entity_backed_browse_buckets_20260928.md). The statement-form fact itself stays on the theorem unchanged.
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Source Hoeffding's inequality, Wikipedia
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Source Hoeffding's inequality, Wikipedia
Sources
1. Wikipedia: Hoeffding's inequality
WikipediaLead section, statement-form referenceQuote, Lead section, statement-form reference
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.
2. Hoeffding's inequality, Wikipedia
Lead section, first sentence
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.
History section
Hoeffding's inequality was proven by Wassily Hoeffding in 1963.
In Branch: Probability and Statistics, Lead sentence
In probability theory, Hoeffding's inequality provides an upper bound on the probability that the sum of bounded independent rando
Proved By: Wassily Hoeffding, Lead paragraph
In probability theory, Hoeffding's inequality provides an upper bound on the probability that the sum of bounded independent random variables deviates from
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