Changes

'''Covariance''' is a measure of the linear dependence of two [[variable]]s. If two variables tend to vary in the same direction, then they have a positive covariance.  If they tend to vary in opposite directions, then they have a negative covariance.

'''Covariance''' is a measure of the linear dependence of two [[variable]]s. If two variables tend to vary in the same direction, then they have a positive covariance.  If they tend to vary in opposite directions, then they have a negative covariance.

The covariance between two random variables ''X'' and ''Y'', having [[expected value]]s <math>\mu</math> and <math>\nu</math> respectively, is as follows:

The covariance between two random variables ''X'' and ''Y'', having expected values <math>\mu</math> and <math>\nu</math> respectively, is as follows:

: <math>\operatorname{Cov}(X, Y) = \operatorname{E}[(X - \mu) (Y - \nu)], \,</math>

: <math>\operatorname{Cov}(X, Y) = \operatorname{E}[(X - \mu) (Y - \nu)], \,</math>

where E is the operator for the [[expectation]].  

where E is the operator for the [[expectation (math)|expectation]].  

If ''X'' and ''Y'' are completely [[statistically independent]] from each other, then they have zero covariance.

If ''X'' and ''Y'' are completely [[statistically independent]] from each other, then they have zero covariance.