Covariance

Measure of the joint variability of two random variables. the sign of the covariance shows the tendency in the linear relationship between the variables. If greater values in one correspond to greater values in the other then this will be a more positive number. The magnitude of the covariance is the Geometric Mean of the variances that are in common for the two random variables (what does this mean???). The formula for covariance of two random variables is $cov(X,Y)=E[(X-E[X])(Y-E[Y])]$. We can see that this is a product of perturbations from expectations across our random variables. we can see covariance as a linear gauge of dependences between two variables, higher abs covariance, higher dependence, lower, more independent.