Normal vs. LaPlace Distributions: Critical Values

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SUMMARY

The discussion focuses on the differences between the Normal distribution and the Laplace distribution, specifically regarding their kurtosis and critical values. The Normal distribution has a kurtosis of 3 (excess kurtosis of 0), while the Laplace distribution has a kurtosis of 6 (excess kurtosis of 3). The participants clarify that the Z-scores for the Laplace distribution are not readily available in literature, and suggest using the inverse CDF formula to calculate critical values. For a standard Laplace distribution with mu = 0 and b = 1/Sqrt(2), the critical values for two-tailed tests can be derived from F-1(0.025).

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  • Understanding of statistical distributions, specifically Normal and Laplace distributions
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kimberley
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Hello all. With the standard caveat that my background is neither in math nor science, I've nonetheless been conducting some further independent study in various areas of statistics that are of interest to me.

With the foregoing as background, I'm trying to appreciate the material difference(s) between the Normal distribution and the Laplace distribution. My understanding thus far is that the principle difference is that an ideal Normal distribution has a Kurtosis of 3/Excess Kurtosis of 0 while a LaPlace distribution has a Kurtosis of 6/Excess Kurtosis of 3. It's also my understanding that each has a Skewness of 0 and their points of Central Tendency are their arithmetic Means.

What I haven't been able to find, however, are the Z-scores/critical values for a LaPlace distribution. By this I specifically mean the two-tailed .01, .05, .3173 levels which, for a standard normal, would be 2.576, 1.96 and 1. Typically, if I'm looking for Z-scores/critical levels for a Normal distribution I specifically use the Student's T Table to get my Z-scores for the given sample size, or use the T Inverse function found in most software. Am I not able to find any literature/tables with regard to these critical levels because they are the same for the Laplace and Normal Distributions, or am I simply not looking in the right place or missing something? Stated in the simplest terms, are 95% of all values in a standard LaPlace distribution +/- 1.96 from the arithmetic mean also? I found one cryptic reference that mentioned 3.842 and 6.635 standard deviations as the .05 and .01 levels for a LaPlace, but frankly I had difficulty following the general topic to attach any weight to the reference.



Your response would be very much appreciated. As always,


Thanks,


Kimberley
 
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kimberley said:
Am I not able to find any literature/tables with regard to these critical levels because they are the same for the Laplace and Normal Distributions,
No!
or am I simply not looking in the right place or missing something?
Laplace is not a "staple" distribution so its tables may be difficult to find. This page tells you the inverse CDF formula F-1. If you assume mu = 0 and b = 1/Sqrt 2, you will have the standard Laplace. To find the 95% value in a two-sided test, just evaluate F-1(0.025). Note, sgn(x) = -1 if x < 0, sgn(x) = 1 if x > 0 and sgn(0) = 0.
Stated in the simplest terms, are 95% of all values in a standard LaPlace distribution +/- 1.96 from the arithmetic mean also?
I'd guess not necessarily.
I found one cryptic reference that mentioned 3.842 and 6.635 standard deviations as the .05 and .01 levels for a LaPlace, but frankly I had difficulty following the general topic to attach any weight to the reference.
You can verify these values by using the inverse CDF formula.
 
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