Calculating Standard Deviation for U(-1,1) Distribution

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SUMMARY

The discussion focuses on calculating the standard deviation of the Uniform distribution U(-1,1), which has a probability density function (p.d.f.) of f(x) = 1/2 for -1 < x < 1. The standard deviation is confirmed to be 1/√3, derived from the variance of 1/3. The Fourier transform of the distribution is calculated as fhat(epsilon) = sin(epsilon)/epsilon, and the standard deviation can be obtained through both integral calculation and power series expansion of the Fourier transform. The mean of the distribution is established as 0, leading to the variance calculation.

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Consider the Uniform distribution (continuous) U(-1,1) which has p.d.f. f(x) = 1/2 for -1 < x < 1 and 0 otherwise.

I have calculated the Fourier transform using the characteristic function and got fhat(epsilon)= sin(epsilon)/epsilon

How do I calculate the standard deviation of this distribution using both the Fourier transform and the definition. I know that the standard deviation is 1/sqrt(3) but how do I get this using what's above.
 
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The simplest method is to calculate the integral of x2 with respect to the density function you are given (=1/3). Since the mean = 0, the variance = 1/3 and the standard deviation = 1/√3. You could expand fhat into a power series and the coefficient of the x2 term gives the second moment (there may be a factor here).
 
By definition fhat(t)=E[exp(itX)] so if you expand exp(itX) in a Taylor series you'll get an expression for the moments in terms of the Taylor series of fhat.
 

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