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Covariance is a quantity used to measure the strength and direction of the linear relationship between two variables. The covariance is unscaled, & thus often difficult to interpret; when scaled by the variables' SDs, it becomes Pearson's correlation coefficient.
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Distribution of correlation coefficient in compound symmetric covariance model
Letting $S$ be the standard sample covariance matrix, (that is, $S = \frac{1}{n}\sum_{i=1}^n (X_i - \bar{X})^T(X_i -\bar{X})$) Muirhead (1985, p114) shows that the MLE for $\rho$ is given by
$$ \hat\rho …
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Find covariance when expected value of product is zero
As you correctly state,
$$ {\rm Cov}(W, X) = E(WX) - E(W) E(X). $$
If you are given that $E(XW) = 0$, then ${\rm Cov}(W, X) =0 \iff E(W) = 0$ or $E(X) = 0$. Perhaps you should consider whether either …