is about expected value variable covariance 2 2 cov(x, y = NULL, use = "everything", method = c("pearson", "kendall", "spearman")) from: http://stat.ethz.ch/R-manual/R-patched/library/stats/html/cor.html Alejandra Gonzalez-Beltran Orlaith Burke Philippe Rocca-Serra The covariance is a measurement data item about the strength of correlation between a set (2 or more) of random variables. The covariance is obtained by forming: cov(X,Y)=E([X-E(X)][Y-E(Y)] where E(X), E(Y) is the expected value (mean) of variable X and Y respectively. covariance is symmetric so cov(X,Y)=cov(Y,X). The covariance is usefull when looking at the variance of the sum of the 2 random variables since: var(X+Y) = var(X) +var(Y) +2cov(X,Y) The covariance cov(x,y) is used to obtain the coefficient of correlation cor(x,y) by normalizing (dividing) cov(x,y) but the product of the standard deviations of x and y. adapted from: http://mathworld.wolfram.com/Covariance.html covariance measure of correlation ready for release