Timeline for Does the variance of a sum equal the sum of the variances?
Current License: CC BY-SA 3.0
14 events
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| Oct 17, 2021 at 21:33 | comment | added | Josh Albert | @Abe the condition that should be met for variance of the sum of correlated RVs to be the sum of variance is that the sum of the off-diagonals is zero. | |
| Jun 28, 2012 at 1:12 | history | edited | Macro | CC BY-SA 3.0 |
cleaned up odd notation in E( sum(X) )^2 vs. E( sum(X)^2 )
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| S Jun 27, 2012 at 18:06 | history | suggested | Abe | CC BY-SA 3.0 |
changed example matrix for clarity as explained in my comment
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| Jun 27, 2012 at 18:05 | review | Suggested edits | |||
| S Jun 27, 2012 at 18:06 | |||||
| Jun 27, 2012 at 17:56 | comment | added | Abe | Regarding the example covariance matrix, is the following correct: the symmetry between the upper right and lower left triangles reflects the fact that $\text{cov}(X_i,X_j)=\text{cov}(X_j,X_i)$, but the symmetry between the upper left and the lower right (in this case that $\text{cov}(X_1, X_2) = \text{cov}(X_2,X_3) = 0.3$ is just part of the example, but could be replaced with two different numbers that sum to $0.6$ e.g., $\text{cov}(X_1, X_2) = a$ and $\text{cov}(X_2,X,3) = 0.6 -a$? Thanks again. | |
| Jun 27, 2012 at 17:44 | vote | accept | Abe | ||
| Jun 27, 2012 at 2:37 | history | edited | Dilip Sarwate | CC BY-SA 3.0 |
corrected minor typos
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| Jun 27, 2012 at 0:53 | history | edited | Macro | CC BY-SA 3.0 |
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| Jun 26, 2012 at 22:51 | history | answered | Macro | CC BY-SA 3.0 |