Probability theory and stochastic processes Theorem
Linearity of expectation
Builds on Expected value
Statement
Let and be integrable real random variables on one probability space, and let . Then is integrable and
Remarks
The statement is the linearity of the Lebesgue integral. It holds for all integrable and , also when they are not independent. By induction, . A standard use is the method of indicators. If counts how many of the events occur, then and . For nonnegative random variables, additivity holds without integrability, in .
Reading path
To understand this page from the ground up, read these 44 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 space definition
- Random variable definition
- Discrete random variable definition
- Random variable with a density definition
- Expected value definition
- Linearity of expectation statement
Where this leads
63 pages build on this one.
- Law of total variance
- Variance of the normal distribution
- Variance under translation
- Method of moments
- Weak law of large numbers
- Variance of a sum
- Strong law of large numbers
- Chi-squared test
- Maximum likelihood estimation
- Student's t-test
- Sample variance
- Confidence interval
- Variance under scaling
- Coupon collector's problem
- Variance as the mean of the square minus the square of the mean
- Student's t-distribution
- Expectation with respect to the binomial distribution
- Sample mean
- Chi-squared distribution
- Variance of a sum of independent random variables
- Efficiency of an estimator
- Poisson regression
- Ergodic decomposition
- Koksma–Hlawka inequality
- Hodges' superefficient estimator
- Consistency of the maximum likelihood estimator
- M-estimator
- Score test
- Kingman's subadditive ergodic theorem
- Asymptotic normality of the maximum likelihood estimator
- F-distribution
- Sample mean and sample covariance
- Whittle likelihood
- Logistic regression
- Monte Carlo integration
- Breakdown point
- Noncentral chi-squared distribution
- Behrens–Fisher problem
- Kruskal–Wallis test
- Wishart distribution
- Empirical likelihood
- Bayesian information criterion
- Cochran's theorem
- Jackknife
- Birkhoff's ergodic theorem
- Akaike information criterion
- Independence of sample mean and sample variance for normal samples
- Estimating equations
- Generalized method of moments
- Oseledets theorem
- Likelihood-ratio test
- Expectation–maximization algorithm
- Hotelling's T-squared distribution
- Wald test
- Generalized linear model
- Box–Jenkins method
- Pesin theory
- Binomial proportion confidence interval
- Neyman construction
- Wilks' theorem
- Frequentist inference
- Observed information
- Point estimation
Further reading
- Web https://en.wikipedia.org/wiki/Expected_value, Properties
About this page
| Tag | 0P7PTC8DDE |
|---|---|
| URI | m2://0P7PTC8DDE |
| Aliases | expectation-is-linear |
| Kind | statement, theorem |
| Writing | W0 stub |
| MSC | 60A05 |
| Status | This copy of the site has no build data. Run m2 status 0P7PTC8DDE. |
| Uses | Expected value |
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