law of large numbers

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law of large numbers

[′lȯ əv ¦lärj ′nəm·bərz]
(statistics)
The law that if, in a collection of independent identical experiments, N (B) represents the number of occurrences of an event B in n trials, and p is the probability that B occurs at any given trial, then for large enough n it is unlikely that N (B)/ n differs from p by very much. Also known as Bernoulli theorem.
References in periodicals archive ?
One of the laws of large numbers that actually worked was the one that says if you write a lot of bad business you get large, crippling losses.
One thing to be clear about is that there is no conflict, as has sometimes been claimed, between the various laws of large numbers and von Mises' theory.
To this extent von Mises' own axiom of randomness is a virtue, not a vice of his theory, enabling it to deliver the weak and other laws of large numbers without additional special hypotheses of independence and constant probability.