Normal Distribution, Why is it "Normal"?

Описание: Course Content
1) Exploratory Data Analysis
2) Probability Theory
3) Random Variables
4) Distributions
5) Generating Functions
6) Joint Distributions
7) Conditional Expectations
8) CLT
9) Sampling & Inference
10) Point Estimation
11) Confidence Intervals
12) Hypothesis Testing
13) Regression and Correlation
14) ANOVA

For exams:
Exam P
CS1
Formerly CT3

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Normal Distribution, what makes it Normal?

The Normal Distribution is Bell shaped continuous distribution.
It is also known as the Gaussian Distribution.

Although Gauss was a very intelligent man, he didn’t discover it.
Same with the Poisson Distribution, Simon Poisson, didn’t discover it.

Both of these distributions were most likely discovered by Abraham De Moive.
He was an absolute genius but was always outshone by his best friend, Isaac Newton.

Anyway, Abraham would plot the results of multiple binomial Distribution simulations and he found a pattern that resembled a bell shape. This discovery led to the Central Limit Theorem and the birth of Modern Statistics.

This curve would become so famous that it would get the name normal.
Normal means usual, typical, expected.

Again and Again, people would plot data and see the bell curve.
It was to be expected, it was normal.

However, Mandlebrot, the guy who discovered Fractals, warned the world that financial prices were not normal. In fact, he said they were an example of wild randomness and had infinite variance.

The world ignored him because the normal distribution worked so well with models, it had so much mathematical support. An infinite variance would break the actuarial models and so regulators stuck with the normal models to calculate their risk.

Thus the financial world underestimated the Risk and it was a big stuff up.
Mandelbrot died in 2010 which meant he got to see the world make one the biggest mistakes.

I wonder if his last words were, I told you so.