Probability theory and stochastic processes Inequalities Theorem
Chebyshev's inequality
Statement
Let be a real random variable with finite mean and finite variance . Then for each , Equivalently, if , then for each .
Remarks
Proof: apply Markov's inequality to the nonnegative variable and the level . For , at least of the mass is within two standard deviations of the mean, for every distribution with finite variance. The bound is sharp: some distributions reach equality for a given . Chebyshev's inequality gives a short proof of the weak law of large numbers for variables with finite variance.
History
The inequality is named after Pafnuty Chebyshev. Irénée-Jules Bienaymé formulated it first.
Reading path
To understand this page from the ground up, read these 53 pages in order. The foundations come first.
- Construction of the reals from Cauchy sequences concept
- Element definition
- Integers object
- Ordered field definition
- Proposition concept
- Random experiment concept
- Rational numbers object
- Real numbers object
- Set bounded above definition
- Set definition
- Ring of integers statement
- Disjunction definition
- Implication definition
- Predicate definition
- Supremum definition
- Ordered pair definition
- Union definition
- Sample space definition
- The rationals form a field statement
- Existential quantifier definition
- Universal quantifier definition
- Completeness axiom statement
- Cartesian product definition
- Subset definition
- The rationals form an ordered field statement
- Uniqueness quantifier definition
- Existence of square roots of nonnegative reals statement
- Binary relation definition
- Universal set definition
- Order on the reals definition
- Power set definition
- Square root definition
- Complement definition
- Function definition
- Interval definition
- Injective function definition
- Preimage of a set definition
- Sigma-algebra definition
- Countable set definition
- Event definition
- Borel sigma-algebra definition
- Probability axioms concept
- Probability measure definition
- Probability space definition
- Monotonicity of probability statement
- Random variable definition
- Discrete random variable definition
- Random variable with a density definition
- Expected value definition
- Markov's inequality statement
- Variance definition
- Standard deviation definition
- Chebyshev's inequality statement
Where this leads
11 pages build on this one.
- Weak law of large numbers
- Strong law of large numbers
- Ergodic decomposition
- Koksma–Hlawka inequality
- Consistency of the maximum likelihood estimator
- Kingman's subadditive ergodic theorem
- Asymptotic normality of the maximum likelihood estimator
- Monte Carlo integration
- Birkhoff's ergodic theorem
- Oseledets theorem
- Pesin theory
Further reading
- Web https://en.wikipedia.org/wiki/Chebyshev's_inequality, Probabilistic statement
About this page
| Tag | 02HZ1BK3MW |
|---|---|
| URI | m2://02HZ1BK3MW |
| Aliases | bienayme-chebyshev-inequality |
| Kind | statement, theorem |
| Writing | W1 stated |
| MSC | 60E15 |
| Status | This copy of the site has no build data. Run m2 status 02HZ1BK3MW. |
| Uses | Markov's inequality, Variance, Standard deviation |
| Same as |
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