The Normal Curve

 

You know, there’s been this flip question floating around for a few centuries as to whether Mathematics measures a Real World.

Or is it just us painting with a palette limited to the colors we can see [like the visible .30 % of the Electromagnetic Spectrum]. And then claiming we’ve caught the ghost in our picture.

Sort of like the Nobel Committee limiting the Literature Prize to a Writer writing in a language it can read [about 5 out of around 7,000].

Same thing here. Most of the testing talked about in the previous post is grounded on the perfectly symmetric Gaussian Curve [the ‘Normal Distribution’: see the Diagram].

It is arguably the most widely used tool in Applied Mathematics. Various theorems prove that all things sampled in sufficiently large quantities converge to the Gaussian Curve. 

The Curve is conceived on a binary platform and mounted on the critical assumption [among others] of ‘Independent, Separate Observations’, a fairly dodgy idea but embraced in the Scientific community as perfectly realistic and sensible.

Is this the way Nature really curves? Or is this the only way Nature knows to curve given how how we’ve rigged the rules, given how we think?

Is this Grandma being nice to her adorable grandson before he throws another fit?


‘What we observe is not Nature in itself but Nature exposed to our method of questioning’ noted Heisenberg [who was very familiar with the old Gaussian Curve].