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The expected squared deviation of a random variable from its mean; or, the average squared deviation of data about their mean.

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Law of total covariance with multiple conditionals

The law of total covariance states: $Cov(X,Y) = E(Cov(X,Y|Z)) + Cov(E(X|Z),E(Y|Z))$ If I condition on another variable $T$, does this still hold? E.g. $Cov(X,Y) = E(Cov(X,Y|Z,T)) + Cov(E(X|Z,T),E(Y …
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