Standard deviation of series of trials

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Gauss M.D.
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Say we want to saw ten planks and we have two methods available - one is sawing them all at once, ensuring they're all exactly uniform length. The other method is sawing them individually. Either method has EV of 1m and a standard deviation of 0.005m. I want to find the standard deviation of both methods.

In other words, given a random variable X, I guess what we're trying to figure out is SD(10X) and SD(X1 + X2 + ... + X10).

I'm not sure how to calculate the second one. Anyone want to give me a push? :S
 
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[tex]\operatorname{SD}(A + B + \cdots + Z) = \sqrt{\operatorname{SD}(A)^2 + \operatorname{SD}(B)^2 + \cdots + \operatorname{SD}(Z)^2}[/tex]

What this basically says is that the variance Var(X) = SD(X)² is linear:
[tex]\operatorname{Var}(A + B + \cdots + Z) = \operatorname{Var}(A) + \operatorname{Var}(B) + \cdots + \operatorname{Var}(Z)[/tex]

Also note that by setting A = B = ... = X you can actually derive the result for SD(10X).