Conditional variance: Difference between revisions

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In words: the variance of ''Y'' is the sum of the expected conditional variance ''Y'' given ''X'' and the variance of the conditional expectation of ''Y'' given ''X''. The first term captures the variation left after "using ''X'' to predict ''Y''", while the second term captures the variation due to the mean of the prediction of ''Y'' due to the randomness of ''X''.

==See also==

*[[Mixed model]]

*[[Random effects model]]

==References==