Probability theory and stochastic processes Theorem
Law of the unconscious statistician
Builds on Expected valueLaw of a random variableProbability mass functionProbability density function
Statement
Let be a random variable on with values in and with law . Let be measurable. Then is integrable if and only if . In that case, In particular, if is discrete with mass function , then . If is real with density , then .
Remarks
The formula also holds for without any integrability condition, with both sides in . The proof checks the formula first for indicator functions , where it says . Then it extends to simple, nonnegative and integrable . The point is that one does not need the law of to compute .
History
The name refers to statisticians who use the formula as the definition of . They are "unconscious" that it is a theorem that needs a proof.
Reading path
To understand this page from the ground up, read these 49 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 definition
- Ring of integers statement
- Disjunction definition
- Implication definition
- Predicate definition
- Ordered pair definition
- Union definition
- Sample space definition
- The rationals form a field statement
- Existential quantifier definition
- Universal quantifier definition
- Cartesian product definition
- Subset definition
- The rationals form an ordered field statement
- Uniqueness quantifier definition
- Binary relation definition
- Universal set definition
- Order on the reals definition
- Power set 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 distribution definition
- Probability space definition
- Random variable definition
- Cumulative distribution function definition
- Discrete random variable definition
- Law of a random variable definition
- Random variable with a density definition
- Probability mass function definition
- Expected value definition
- Probability density function definition
- Law of the unconscious statistician statement
Where this leads
33 pages build on this one.
- Chernoff bound
- Characteristic function of a sum of independent random variables
- De Moivre–Laplace theorem
- Method of moments
- Moment-generating function of the normal distribution
- Kurtosis
- Central limit theorem
- Lévy's continuity theorem
- Skewness
- Characteristic function
- Moment-generating function
- Characteristic function of the normal distribution
- Sum of independent normal random variables
- Moment
- Cumulant generating function
- Moments are derivatives of the moment-generating function at zero
- The characteristic function determines the distribution
- Hoeffding's inequality
- Moment-generating function of a sum of independent random variables
- Central moment
- Koksma–Hlawka inequality
- Cramér–Wold theorem
- McDiarmid's inequality
- Asymptotic normality of the maximum likelihood estimator
- Edgeworth expansion
- Azuma's inequality
- Erdős–Kac theorem
- Monte Carlo integration
- Delta method
- Berry–Esseen theorem
- Estimating equations
- Generalized method of moments
- Bernstein inequalities
Further reading
- Web https://en.wikipedia.org/wiki/Law_of_the_unconscious_statistician, Measure-theoretic formulation
About this page
| Tag | 01ZWX875AT |
|---|---|
| URI | m2://01ZWX875AT |
| Aliases | lotus, change-of-variables-formula-for-expectation |
| Kind | statement, theorem |
| Writing | W0 stub |
| MSC | 60A05 |
| Status | This copy of the site has no build data. Run m2 status 01ZWX875AT. |
| Uses | Expected value, Law of a random variable, Probability mass function, Probability density function |
| Same as |
Markdown · JSON · Edit on GitHub
What this page needs for W1
- an inventory row: the row of the inventory that the node accounts for (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.