Mental Blank / Hopefully easy question

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The inequality Var[X] + Var[Y] - 2Cov(X,Y) > 0 is established as a fundamental property in statistics, derived from the non-negativity of the squared difference (X - Y)^2. This relationship holds true as it simplifies to the expression involving variance and covariance, confirming that the variance of the difference between two random variables cannot be negative. The derivation involves substituting the definitions of variance and covariance, leading to a clear understanding of the inequality's validity.

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patata
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Hi all,

Probably a stupid question, but in general, is it true that Var[x] + Var[Y] -2Cov(X,Y) > 0? I'm having trouble figuring out why a number of articles I seem to have read take this for granted without demonstrating why (which makes me think it could be fairly trivial...).

Thanks for any help!
 
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You can derive it from (x-y)^2 >=0
It can be equal to zero, but not negative. Just plug in the definitions of variance and covariance and simplify until you get something like (x-y)^2.
 
If you start with {(X - mx) - (Y-my)}2, it follows immediately. (The m's are means).
 

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