Standard deviation of expectation values

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neu
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Very basic question which has confused me:

if the variance of an expectation value <A> is:

uncertainty of [tex]A=<(A-<A>)^2>^0.5[/tex]

how is this equal to:

[tex](<A^2>-<A>^2)^0.5[/tex]

??
 
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Expand it out:
[tex]<(A-<A>)^2> = < A^2 - 2A<A> + <A>^2 > = < A^2 - <A>^2 >[/tex]
 
Start by expanding the squared term in parentheses:

[itex](A - <A>)^2 = A^2 - 2<A>A + <A>^2[/itex]

Note that <A> is simply a number and can be manipulated like any other numeric constant. Simplify the resulting expectation value by taking advantage of general properties of expectation values, i.e.

[itex]<A+B> = <A> + <B>[/itex]

[itex]<cA> = c<A>[/itex]

where c is a numeric constant.