is about
measurement datum
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
ready for release