Is this a coincidence that this looks like a Gaussian?

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SUMMARY

The discussion confirms that the observed pattern resembling a Gaussian distribution is coincidental, attributed to moisture wicking through render, leading to mold or algae growth. The conversation highlights that many natural relationships between variables can appear linear, quadratic, exponential, sinusoidal, or Gaussian depending on the scaling of axes. It emphasizes the importance of initial curve fitting in scientific analysis, while also noting that the observed data does not meet the criteria for a true Gaussian distribution due to its pointedness.

PREREQUISITES
  • Understanding of Gaussian distributions and their properties
  • Familiarity with data visualization techniques
  • Knowledge of moisture dynamics in building materials
  • Basic statistical analysis concepts
NEXT STEPS
  • Research the properties of Gaussian distributions in detail
  • Explore data visualization tools for better representation of variable relationships
  • Study moisture wicking and its effects on building materials
  • Learn about statistical curve fitting techniques and their applications
USEFUL FOR

This discussion is beneficial for statisticians, data analysts, building engineers, and anyone interested in understanding the nuances of data representation and moisture effects in construction.

GLD223
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Welcome to PF.

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:
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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