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

In summary, the Uniform distribution (continuous) U(-1,1) with p.d.f. f(x) = 1/2 for -1 < x < 1 and 0 otherwise can be used to calculate the standard deviation using both the Fourier transform and the definition. The simplest method is to calculate the integral of x2 with respect to the given density function, which results in a standard deviation of 1/√3. Alternatively, fhat can be expanded into a power series to find the second moment. By definition, fhat is equal to the expected value of exp(itX), so expanding exp(itX) in a Taylor series can provide an expression for the moments in terms of the Taylor series of fhat
  • #1
squenshl
479
4
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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  • #2
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).
 
  • #3
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.
 

1. What is the formula for calculating standard deviation for a uniform distribution with range -1 to 1?

The formula for calculating standard deviation for a uniform distribution with range -1 to 1 is √(1/12 * (1-(-1))^2) = √(1/12 * 4) = √(1/3) = 0.5774.

2. How is the standard deviation different from the mean for a uniform distribution?

The standard deviation measures how spread out the data is from the mean, while the mean represents the average value of the data. For a uniform distribution, the mean is always 0, but the standard deviation can vary depending on the range of the distribution.

3. Can the standard deviation for a uniform distribution with range -1 to 1 be negative?

No, the standard deviation cannot be negative. It is always a positive value that represents the average amount of deviation from the mean.

4. How does the range of the distribution affect the standard deviation?

The larger the range of the distribution, the larger the standard deviation will be. This is because a larger range means a wider spread of data, resulting in a higher average deviation from the mean.

5. Is there a quick way to calculate the standard deviation for a uniform distribution with range -1 to 1?

Yes, for a uniform distribution with range -1 to 1, the standard deviation can be calculated by simply dividing the range (2) by √12, which is approximately 3.4641.

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