Random variables are independent when their generated sigma-algebras are independent sigma-algebras. Equivalently, their joint distribution is the product of their marginal distributions.
Ancestors
Incoming links
- Completely noisy binary symmetric channel
- Conditioning reduces entropy
- Entropy of a sum of independent finite-group variables
- Independent and identically distributed random variables
- Kolmogorov zero-one law
- M-M-infinity queue
- One-time pad
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- Perfect secrecy
- Probability generating function
- Running minimum of an independent sequence is Markov
- Simultaneous returns of independent simple random walks
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