Seonglae ChoEve's law
Variance decomposition formula, conditional variance formulas or law of iterated variances
expectation of variance + variance of expectation
EVPV(expected value of the process variance) + VHM (variance of the hypothetical means)
The average variability of Y according to changes in X + The remaining uncertainty of Y even after knowing X
XY 2차원 분포 생각하면 이해 편하다 - E[], V[] 결과가 상수가 아니라 함수로 나옴 적분위해
Decomposes the variance of two random variables on the same probability space into explained and unexplained components
Law of total variance
In probability theory, the law of total variance[1] or variance decomposition formula or conditional variance formulas or law of iterated variances also known as Eve's law,[2] states that if
X
{\displaystyle X}
and
Y
{\displaystyle Y}
are random variables on the same probability space, and the variance of
Y
{\displaystyle Y}
is finite, then
https://en.wikipedia.org/wiki/Law_of_total_variance