Probability theory and stochastic processes Concept
Independence of random variables
Summary
A family of random variables is independent, or mutually independent, when events about different members of the family are always mutually independent. The node independence of random variables gives the precise definition.
Where this leads
11 pages build on this one.
Further reading
- Web https://en.wikipedia.org/wiki/Independence_(probability_theory), More than two random variables
About this page
| Tag | 0GQ938GDE0 |
|---|---|
| URI | m2://0GQ938GDE0 |
| Aliases | mutually-independent-random-variables |
| Kind | concept |
| Writing | W1 stated |
| MSC | 60A05 |
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What this page needs for W2
- edge instance_of in: at least two examples (0 of 2)
- edge not_instance_of in: at least one non-example (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.
What links here
Special cases
Definitions
Used by
- Rubin causal model
- McDiarmid's inequality
- Box–Muller transform
- Marcinkiewicz–Zygmund inequality
- Lévy process
- Kolmogorov's inequality
- Lindeberg's condition
- Stratified sampling
- Bernstein inequalities
- Kolmogorov's three-series theorem
- Independent component analysis