Posts tagged with normal curve

Central Limit Theorem
A nice illustration of the Central Limit Theorem by convolution.in R:
Heaviside <- function(x) {      ifelse(x>0,1,0) }HH <- convolve( Heaviside(x), rev(Heaviside(x)),        type = "open"   )HHHH <- convolve(HH, rev(HH),   type = "open"   )HHHHHHHH <- convolve(HHHH, rev(HHHH),   type = "open"   )etc.
What I really like about this dimostrazione is that it’s not a proof, rather an experiment carried out on a computer.
This empiricism is especially cool since the Bell Curve, 80/20 Rule, etc, have become such a religion.NERD NOTE:  Which weapon is better, a 1d10 longsword, or a 2d4 oaken staff? Sometimes the damage is written as 1-10 longsword and 2-8 quarterstaff. However, these ranges disregard the greater likelihood of the quarterstaff scoring 4,5,6 damage than 1,2,7,8. The longsword’s distribution 1d10 ~Uniform[1,10], while 2d4 looks like a Λ.
(To see this another way, think of the combinatorics.)

Central Limit Theorem

A nice illustration of the Central Limit Theorem by convolution.

in R:

Heaviside <- function(x) {      ifelse(x>0,1,0) }
HH <- convolve( Heaviside(x), rev(Heaviside(x)),        type = "open"   )
HHHH <- convolve(HH, rev(HH),   type = "open"   )
HHHHHHHH <- convolve(HHHH, rev(HHHH),   type = "open"   )
etc.


What I really like about this dimostrazione is that it’s not a proof, rather an experiment carried out on a computer.

This empiricism is especially cool since the Bell Curve, 80/20 Rule, etc, have become such a religion.




NERD NOTE:  Which weapon is better, a 1d10 longsword, or a 2d4 oaken staff? Sometimes the damage is written as 1-10 longsword and 2-8 quarterstaff. However, these ranges disregard the greater likelihood of the quarterstaff scoring 4,5,6 damage than 1,2,7,8. The longsword’s distribution 1d10 ~Uniform[1,10], while 2d4 looks like a Λ.

(To see this another way, think of the combinatorics.)


hi-res




(A Lévy-Pareto process has infinite variance.)

comptes_rendus_28

Cauchy distribution

Cauchy distribution

  • has infinite variance
  • as contrasted to…

Gaussian distribution

which shoots down REAL fast: e^ &minus; x&sup2; fast.