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A statistic which measures the agreement between two sets of data. For variables X and Y, with means x and y, the covariance is Cov(X,Y)=E(XY)-xy.
The covariance of two samples of equal size x_i, y_i is: c_xy = ∑_i [1/(n)] ( x_i − [(x)] )( y_i − [(y)] ) .
Covariance depends on the scale used to make the measurements, unlike correlation, which is another measure of the agreement between sets of data.

The covariance of random variables X and Y is

cov(X,Y) = E ( ( X− E X ) (Y− E Y) ) .

The correlation of X and Y is

corr(X,Y) = cov(X,Y) √ var(X) var(Y) .

It takes values in [−1,1] and indicates the degree of linear correlation between X and Y , with a positive or negative constant of proportionality as corr(X,Y) ≈ ±1