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Covariance is a quantity used to measure the strength and direction of the linear relationship between two variables. The covariance is unscaled, & thus often difficult to interpret; when scaled by the variables' SDs, it becomes Pearson's correlation coefficient.

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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. …
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