Numerical Calculation of \Gamma = 2.354 \sigma

In summary, the conversation discusses the concept of data reduction and the calculation of the full-width at half maximum (FWHM) for a Gaussian probability distribution. The numerical calculation for this relationship is related to the approximation of 2.354 for the standard deviation. The conversation also mentions a proof for the relationship between FWHM and the standard deviation and asks for the x value at which the Gaussian reaches half maximum.
  • #1
tony873004
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For starters... What does "data reduction" mean? The book starts throwing around this term (which is also part of the book's title) without even defining it.

homework question:

Show by numerical calculation that, for the Gaussian probability distribution, the full-width at half maximum [tex]\Gamma[/tex] is related to the standard deviation by [tex]\Gamma=2.354 \sigma[/tex].

What is a numerical calculation? Does this just mean "do the math", or does it mean numerical as in numerical vs. analytic methods, where I'm supposed to make the computer crunch a whole bunch of otherwise-unmanagable numbers to get an answer?

Any idea how to do this problem? I know that the standard deviation is equal to the square root of the mean. And I know that the full-width, half max is equal to the width of the curve halfway to the top of the curve. But I don't see a formula for computing it. When describing it, the book gives [tex]p_G \left( {\mu \pm 1/2\Gamma ,\mu ,\sigma } \right) = 1/2p_G \left( {\mu ;\mu ,\sigma } \right)[/tex]

There's a nice graph in the book showing standard deviation and FWHM, where eye-balling it, 2.354 seems like reasonable number.
 
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  • #2
data reduction is just the process of transforming data to a more usable form (binning, averaging, etc.).

Here I think the numerical calculation part is due to the fact that 2.354 is only an approximation.

The proof for the relationship between the FWHM and the std. dev. isn't overly difficult. As a starter, what is the x value for which the gaussian reaches half maximum?
 
  • #3
link2001 said:
data reduction is just the process of transforming data to a more usable form (binning, averaging, etc.).

Here I think the numerical calculation part is due to the fact that 2.354 is only an approximation.

The proof for the relationship between the FWHM and the std. dev. isn't overly difficult. As a starter, what is the x value for which the gaussian reaches half maximum?

Thanks. We talked about this in class today. I'm starting to get it.
 

1. What is the significance of the value of \Gamma = 2.354 \sigma in numerical calculations?

The value of \Gamma = 2.354 \sigma is commonly known as the full width at half maximum (FWHM) in statistics and signal processing. It represents the width of a peak at half of its maximum height in a normal distribution or frequency spectrum.

2. How is \Gamma = 2.354 \sigma used in numerical calculations?

In numerical calculations, \Gamma = 2.354 \sigma is used to determine the standard deviation (\sigma) of a normal distribution or frequency spectrum. It is also used to calculate the width of a peak or the distance between two peaks.

3. Can the value of \Gamma = 2.354 \sigma be derived from other statistical measures?

Yes, the value of \Gamma = 2.354 \sigma can be derived from other statistical measures such as the variance, which is equal to \sigma^2, and the standard deviation, which is equal to \sigma. It can also be derived from the mean and the median of a dataset.

4. How is \Gamma = 2.354 \sigma related to the normal distribution curve?

The value of \Gamma = 2.354 \sigma is directly related to the shape of the normal distribution curve. It represents the distance between the inflection points of the curve, where the slope changes from positive to negative or vice versa.

5. Are there any limitations to using \Gamma = 2.354 \sigma in numerical calculations?

While \Gamma = 2.354 \sigma is a useful measure in numerical calculations, it is based on the assumption of a normal distribution. Therefore, it may not accurately represent the width of peaks in non-normal distributions or frequency spectra.

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