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In probability theory, the expected value (also called expectation, mean, or first moment) is a generalization of the weighted average. Provided that it is finite, the expected value can be interpreted as the long-run average of results from independent repetitions of the same random experiment, as formalized by the law of large numbers.
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Expected value | is a | weighted average of those values | 0.90 | text |
| Expected value | is a | linear form on this vector space.Monotonicity | 0.90 | text |
| Expected value | has application | The | 0.60 | section |
| Expected value | has application | In | 0.60 | section |
| Expected value | related to Arbitrary real-valued random variables | All | 0.60 | section |
| Expected value | related to Arbitrary real-valued random variables | In | 0.60 | section |
| Expected value | related to Arbitrary real-valued random variables | Omega | 0.60 | section |
| Expected value | related to Arbitrary real-valued random variables | Sigma | 0.60 | section |
| Expected value | related to Arbitrary real-valued random variables | Lebesgue | 0.60 | section |
| Expected value | related to Arbitrary real-valued random variables | Despite | 0.60 | section |
| Expected value | related to Arbitrary real-valued random variables | This | 0.60 | section |
| Expected value | related to Arbitrary real-valued random variables | Moreover | 0.60 | section |
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