Binomial(n, p) is the probability distribution of the number of "successes" in n independent trials whereby each trial has a binary outcome ("success" or "failure") with the "success" probability p.
If n is large and p is close to 0, then Binomial(n, p) can be approximated by a Poisson(λ) distribution with λ=np.
If n is large and p is far from 0 or 1, then Binomial(n, p) can be approximated by a Gaussian distribution with mean np and variance np(1-p).
@0foldcv Hey I know about that! I learned it from the Universe! :D
@0foldcv I didn't know about the approximations with others though, thanks! :D
@codepuppy The Gaussian approximation follows from the Central Limit Theorem, because a binomial(n,p) random variable X is a sum of n coin tosses.
However, I just learned about the Poisson approximation yesterday; it follows by taking the limit n to infinity of P(X = k) when the product np=λ is kept constant as n goes to infinity (i.e. p goes to 0 at a certain rate).
@0foldcv Oh cool! :D
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