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'''Covariance''' is a measure of the linear dependence of two [[random 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.
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'''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 value]]s <math>\mu</math> and <math>\nu</math> respectively, is as follows:
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where E is the operator for the [[expected value]].  
 
where E is the operator for the [[expected value]].  
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If ''X'' and ''Y'' are completely statistically independent from each other, then they have zero covariance.
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If ''X'' and ''Y'' are completely [[statistically independent]] from each other, then they have zero covariance.
    
Note that if ''X'' and ''Y'' have covariance zero, they are un[[correlated]] but are not necessarily independent.
 
Note that if ''X'' and ''Y'' have covariance zero, they are un[[correlated]] but are not necessarily independent.
    
[[category:probability and Statistics]]
 
[[category:probability and Statistics]]
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