Today I Learned

Some of the things I've learned every day since Oct 10, 2016

29: Variance and Covariance

Where the covariance of 2 random variables X, Y is defined to be

\textrm{cov}(X, Y) = \textrm{E}(XY) - \textrm{E}(X)\textrm{E}(Y)

and the variance of a random variable X is defined to be

\textrm{var}(X) = \textrm{E}(X^2) - (\textrm{E}(X))^2

it’s easy to see that the variance of a variable is simply the covariance of that variable with itself.

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