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Sample Covariance


The sample covariance of paired observations (x_i,y_i) for i=1,...,n is commonly defined by

 s_(xy)=1/(n-1)sum_(i=1)^n(x_i-x^_)(y_i-y^_),

where x^_ and y^_ are the two sample means. With independent observations from a population having finite second moments, this denominator makes s_(xy) an unbiased estimator of the population covariance.

Using denominator n instead gives the second mixed sample central moment and is also called sample covariance by some authors. The convention must therefore be stated. Collecting the pairwise sample covariances of a random sample of vectors gives the sample covariance matrix.


See also

Covariance, Covariance Matrix, Sample Mean, Sample Variance

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References

Casella, G. and Berger, R. L. Statistical Inference, 2nd ed. Pacific Grove, CA: Duxbury, 2002.

Cite this as:

Weisstein, Eric W. "Sample Covariance." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/SampleCovariance.html

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