The Normal probability distribution (bell curve) is a psy-op.

It exists because it has beautiful mathematical properties and if we can imagine such a world where we can see 99% of results in 3 standard deviations around a mean - then we have an extraordinary tool.

1) we get to assume the Law of Large Numbers without any validation. Every system and sample set should be thoroughly validated before making this assumption and even if we get there, you can’t exptrapolate out of that sample to the next observation.

The Normal distribution gives the false narrative that the Law of Large numbers can have predictive power.

2) we get to add the random variables at will and still maintain mathematical equivalence if we assume everything continues to conform to the “bell curve”

This puts the problem stated in 1 on steroids. It also gives midwits a framework to publish endless studies without a rubric for proof, providing the “knowledge system” that doesn’t know any better a basis for “data-driven” decision making. Not good.

3) The map becomes the territory and we lose all sense of “tail risk” in systems were trying to understand. When we underestimate the tail risk, we get REKT.

TLDR

Normal distribution:

1. Gives a false sense of predictive power

2. Gives midwits a framework to provide data to abuse the false predictive power

3. Systematically reduces the aperture to understand tail risk.