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  "body": "\n## Definition\n\nLet $(\\Omega, \\mathcal{F}, P)$ be a probability space and let $(S, \\mathcal{S})$ be a measurable space.\nLet $X_1, \\dots, X_n$ be [[random variables|0PNRKMRC55]] on $\\Omega$ with values in $S$.\nThe finite sequence $(X_1, \\dots, X_n)$ is *exchangeable* if for every [[permutation|05RWFKVTJ7]] $\\sigma$ of $\\set{1, \\dots, n}$ the random vector $(X_{\\sigma(1)}, \\dots, X_{\\sigma(n)})$ has the same [[joint distribution|0DR81R1F2B]] as $(X_1, \\dots, X_n)$.\nAn infinite sequence $X_1, X_2, \\dots$ is *exchangeable* if $(X_1, \\dots, X_n)$ is exchangeable for every $n \\ge 1$.\n\n## Remarks\n\nEquivalently, an infinite sequence is exchangeable if its joint law on $S^{\\N}$ is invariant under every permutation of $\\N$ that moves only finitely many indices.\nExample: if $X_1, X_2, \\dots$ are [[i.i.d.|00MRN0FARV]], the joint law of $(X_1, \\dots, X_n)$ is the product $\\mu^{\\otimes n}$ of the common law $\\mu$, and a product of equal factors does not change when the factors are permuted.\nAnother example: in the [[Pólya urn model|DHPXDFEEMF]], the sequence of colours drawn is exchangeable but not independent.\nNon-example: let $Y$ be a [[Bernoulli|0386Y0Z7Y7]] variable with parameter $\\frac{1}{2}$, and let $X_1 = Y$ and $X_2 = 2Y$.\nThen $P((X_1, X_2) = (1, 2)) = \\frac{1}{2}$ but $P((X_2, X_1) = (1, 2)) = 0$, so the transposition of $1$ and $2$ changes the law.\nEach $X_i$ of an exchangeable sequence has the same law, and each pair $(X_i, X_j)$ with $i \\ne j$ has the same joint law.\n",
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