“…In the second and third editions of his Doctrine of Chances, De Moivre added a section where he presented an approximation for the terms of a binomial expansion which leaded him to an expression which we recognize as the normal curve. The added section was essentially a translation from Latin of a note he had written earlier, which had appeared as a printed pamphlet in 1733 [48][49][50]. In this note, De Moivre considers the middle term of the expansion of (1 + 1)…”
Section: Approximation To the Binomial Expansionmentioning
We examine the concept of probability from its emergence within the realm of the games of chance and the development of the theory of probability until the appearance of the treatise of Kolmogorov on this subject. The discipline related to that theory is framed as the science of aleatory events. Probability is understood as a primitive concept represented by a measure assigned to the space of events and obeying the fundamental postulates of the theory. The measurement of probability is the ratio of the number of the observed favorable outcomes and the total number of observed outcomes when these numbers are larger enough.
“…In the second and third editions of his Doctrine of Chances, De Moivre added a section where he presented an approximation for the terms of a binomial expansion which leaded him to an expression which we recognize as the normal curve. The added section was essentially a translation from Latin of a note he had written earlier, which had appeared as a printed pamphlet in 1733 [48][49][50]. In this note, De Moivre considers the middle term of the expansion of (1 + 1)…”
Section: Approximation To the Binomial Expansionmentioning
We examine the concept of probability from its emergence within the realm of the games of chance and the development of the theory of probability until the appearance of the treatise of Kolmogorov on this subject. The discipline related to that theory is framed as the science of aleatory events. Probability is understood as a primitive concept represented by a measure assigned to the space of events and obeying the fundamental postulates of the theory. The measurement of probability is the ratio of the number of the observed favorable outcomes and the total number of observed outcomes when these numbers are larger enough.
“…The earliest record of the use of the normal distribution appears to be as a convenient approximation to the binomial distribution 1 . This early work, by de Moivre, led to later work by eminent researchers, including Laplace and Gauss, on approximating other distributions using the normal distribution, and ultimately to the construction of the now indispensable central limit theorem (CLT).…”
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