Is a gaussian distribution 'like a sine wave'

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Discussion Overview

The discussion revolves around the comparison between a Gaussian distribution and a sine wave, particularly in the context of their mathematical properties and representations in nature. Participants explore the validity of claims regarding their similarities and differences, touching on concepts from probability distributions and Fourier transforms.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Mathematical reasoning

Main Points Raised

  • One participant argues that while all functions can be represented as sums of sines and cosines via Fourier transforms, this does not imply that all functions behave like sine waves.
  • Another participant suggests that a Gaussian curve could have an identifiable amplitude and period, questioning whether a sine wave could replicate points on a Gaussian curve.
  • Several participants assert that the Gaussian and sine curves are fundamentally different in their behavior and appearance, with the Gaussian being non-negative and tapering off, while the sine oscillates between -1 and +1.
  • One participant highlights that a sine wave cannot serve as a probability distribution function due to its infinite integral, contrasting it with the Gaussian's properties.
  • Another participant notes that both functions are significant in their respective contexts, with sine waves being eigenfunctions of linear systems and Gaussians being eigenfunctions of the Fourier transform.
  • Some participants express confusion over the initial comparison, likening it to comparing unrelated concepts, and seek validation for their views on the differences.
  • A participant questions whether the individual making the comparison can graph both functions to illustrate their differences.

Areas of Agreement / Disagreement

Participants generally agree that Gaussian distributions and sine waves are not alike, with multiple viewpoints presented on the nature of their differences. The discussion remains unresolved regarding the validity of the initial claim that they are similar.

Contextual Notes

Some participants express puzzlement over the initial comparison, suggesting a lack of clarity in understanding the distinct properties of the two functions. The discussion reflects varying levels of familiarity with mathematical concepts related to the functions.

leright
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So I was having a conversation with the guy I share an office with and I brought up the gaussian distribution to show the probability distribution of energies of electrons generated by a filament. He mentioned that it 'looks like a sine wave', and I said 'sorta, but it's not a sine wave'. He said that everything in nature behaves like a sine wave and then I replied that exponentials with imaginary arguments are sine waves, but a gaussian distribution isn't really like a sine wave.

So, is there any truth to my office mate's argument, or is it irrelevant or incorrect to even bring it up?

I suppose all functions can be described by an infinite sum of sines and cosines of a spectrum of frequencies and phases angles using Fourier transforms even if the function isn't periodic, but I can't conclude that this means all functions behave like sines and cosines.

Maybe I am just not understanding his argument. It was probably a waste of time to et into an argument about in the first place, but I thought I'd get your opinion.
 
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Here is a very crude idea:
A gaussian curve should have an identifiable amplitude and identifiable period. Would a sine wave duplicate or nearly enough duplicate the points on the gaussian curve? ...
... See, I told you my idea is very very crude.
 
The Gaussian curve has one max, is always >0 and tails off to 0 as x-> -oo or oo. The sine curve oscillates between -1 and +1 in a completely repetitive way. In no way do they look alike.
 
mathman said:
The Gaussian curve has one max, is always >0 and tails off to 0 as x-> -oo or oo. The sine curve oscillates between -1 and +1 in a completely repetitive way. In no way do they look alike.

Yes, this is the obvious answer and is all I wanted to hear. I was just looking for a second opinion or backup opinion, since this pointless argument dragged on for a while and I wasn't really able to convince him that a Gaussian distribution wasn't really 'like' a sine wave.

Thanks for the support. :)
 
Sure it is. It's kind of wavy.
 
The two functions are nothing at all alike, as mathman says. Furthermore, a probability distribution function must have a finite integral, so a sine wave is not even a valid pdf.

In one sense, though, both sine waves and Gaussians are similarly 'special.' Sine waves are eigenfunctions of the differential equations that govern linear systems, which means that if you put a sine wave into a linear system, you get another sine wave out. Gaussians are the eigenfunctions of the Fourier transform, which means that if you take the Fourier transform of a Gaussian, you get back another Gaussian.

Since linear systems and Fourier transforms exist everywhere in nature (acoustics, optics, electronics, etc.), they are both extremely important.

- Warren
 
leright said:
So I was having a conversation with the guy I share an office with and I brought up the gaussian distribution to show the probability distribution of energies of electrons generated by a filament.

Since the above statement indicates that you are at least somewhat familiar with a Gaussian distribution I find it very puzzling that you failed to notice that it was different to a sine wave. It’s a bit like asking if a gasoline motor and a rodeo clown are sort of the same thing. It would certainly seem a strange question, but even more so if the person asking it was apparently already at least somewhat familiar with both of those items.
 
uart said:
Since the above statement indicates that you are at least somewhat familiar with a Gaussian distribution I find it very puzzling that you failed to notice that it was different to a sine wave. It’s a bit like asking if a gasoline motor and a rodeo clown are sort of the same thing. It would certainly seem a strange question, but even more so if the person asking it was apparently already at least somewhat familiar with both of those items.

no uart, it was clear as day that they were different to me...but I just wanted a second opinion to demonstrate to this person I am arguing with that they are in fact different, since I can't seem to get it through his head no matter what I say.
 
Can this person draw the two functions on paper?

- Warren
 

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