Editing Joint probability distribution (section)

=== Covariance ===
{{Main|Covariance}}

When two or more random variables are defined on a probability space, it is useful to describe how they vary together; that is, it is useful to measure the relationship between the variables. A common measure of the relationship between two random variables is the covariance. Covariance is a measure of linear relationship between the random variables. If the relationship between the random variables is nonlinear, the covariance might not be sensitive to the relationship, which means, it does not relate the correlation between two variables.

The covariance between the random variables <math>X</math> and <math>Y</math> is<ref>{{Cite book|title=Applied statistics and probability for engineers|last=Montgomery, Douglas C.|others=Runger, George C.|isbn=978-1-118-53971-2|edition=Sixth|location=Hoboken, NJ|oclc=861273897|date = 19 November 2013}}</ref>
:<math>\operatorname{cov}(X,Y) = \sigma_{XY}=E[(X-\mu_x)(Y-\mu_y)]=E(XY)-\mu_x\mu_y.</math>