http://en.wikipedia.org/wiki/Variance Decomposition The general formula for variance decomposition or the law of total variance is: If X and Y are two random variables and the variance of X exists, then Here, E(X|Y) is the conditional expectation of X given Y, and Var(X|Y) is the conditional variance of X given Y. (A more intuitive explanation is that given a particular value of Y, then X follows a distribution with mean E(X|Y) and variance Var(X|Y). The above formula tells how to find Var(X) based on the distributions of these two quantities when Y is allowed to vary.) This formula is often applied in analysis of variance, where the corresponding formula is SSTotal = SSBetween + SSWithin. It is also used in linear regression analysis, where the corresponding formula is SSTotal = SSRegression + SSResidual. This can also be derived from the additivity of variances, since the total (observed) score is the sum of the predicted score and the error score, where the latter two are uncorrelated. 请问该如何下手才能推导到SSTotal = SSRegression + SSResidual.呢? 如果是跟统计软体有关请重发文章 如果跟论文有关也烦请您重发文章 文章类别是为了帮助大家搜寻资料与解答，造成不便之处请见谅 --

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