Is this a coincidence that this looks like a Gaussian?

AI Thread Summary
Moisture wicking through render is causing mold or algae growth, particularly on the cool, shaded side of a building. The discussion highlights the complexity of analyzing natural relationships between variables, noting that many can be represented by various mathematical curves such as linear, quadratic, exponential, sinusoidal, or Gaussian. It emphasizes the importance of initial curve fitting in scientific analysis, while also pointing out that not all data conforms to expected Gaussian distributions, illustrated by an anecdote about snowflakes. The conversation reflects on the challenges of accurately interpreting experimental data.
GLD223
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Yes, it is a coincidence.
It looks like moisture is wicking through the render, with a mould or algae growing there.
Is this the cool, shaded side of the building?
What city?
 
GLD223 said:
View attachment 339199View attachment 339200View attachment 339201
Nearly every natural relationship between variables (within some arbitrary range) either looks linear, quadratic, exponential, sinusoidal or gaussian. Change the scales of the x and y axes an you can get a 'convincing fit' (good enough, often to convince a jury).
Don't blame the Scientist who starts off with one of those curves when trying to work out the theory; it's always a good first step.
 
I made a habit out of annoying my experimentalist friends by asking them "Is that a Gaussian?!" every time they were looking at data.
 
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It's not a Gaussian. Too pointy.

I once saw a Gaussian when snowflakes leaked through a slot onto a narrow ledge.
 
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Too kurtotic to be Gaussian
 

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