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In probability theory and statistics, to call two real-valued random variables *X* and *Y* **uncorrelated** means that their correlation is zero, or, equivalently, their covariance is zero.

If *X* and *Y* are independent then they are uncorrelated. It is not true, however, that if they are uncorrelated, they must be independent. For example, if *X* is uniformly distributed on [−1, 1] and *Y* = *X*^{2} then they are uncorrelated even though *X* determines *Y*, and *Y* restricts *X* to at most two values.

Moreover, uncorrelatedness is a relation between only two random variables, whereas independence can be a relationship between more than two.

*See also:* correlation, covariance