#reading-9-probability-concepts
The covariance between two random variables Ri and Rj is the expected value of the cross-product of the deviations of the two random variables from their respective means: Cov(Ri,Rj) = E{[Ri − E(Ri)][Rj − E(Rj)]}. The covariance of a random variable with itself is its own variance.
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Summary ive square root of variance. Standard deviation measures dispersion (as does variance), but it is measured in the same units as the variable.
Covariance is a measure of the co-movement between random variables.
<span>The covariance between two random variables R i and R j is the expected value of the cross-product of the deviations of the two random variables from their respective means: Cov(R i ,R j ) = E{[R i − E(R i )][R j − E(R j )]}. The covariance of a random variable with itself is its own variance.
Correlation is a number between −1 and +1 that measures the co-movement (linear association) between two random variables: ρ(R i ,R j ) = Cov(R i ,R j )/[σ(R i ) σ(R j ) Summary
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