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The law of Large number
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The law of Large number

Creator
Creator
Seonglae Cho
Created
Created
2023 Mar 7 2:41
Editor
Editor
Seonglae Cho
Edited
Edited
2024 Dec 5 14:22
Refs
Refs
Central Limit Theorem
De Moivre - Laplace Theorem

LLN

When
iid
, which

Condition

Basically requires
iid
however
Ergodicity
or

Variance

Since it is
iid
In other words, as , the variance goes to zero.
 
 
De Moivre–Laplace theorem
In probability theory, the de Moivre–Laplace theorem, which is a special case of the central limit theorem, states that the normal distribution may be used as an approximation to the binomial distribution under certain conditions. In particular, the theorem shows that the probability mass function of the random number of "successes" observed in a series of independent Bernoulli trials, each having probability of success, converges to the probability density function of the normal distribution with mean and standard deviation , as grows large, assuming is not or .
De Moivre–Laplace theorem
https://en.wikipedia.org/wiki/De_Moivre–Laplace_theorem
De Moivre–Laplace theorem
 
 

Table of Contents
LLNConditionVariance

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The law of Large number
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