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According to the de Moivre–Laplace theorem, as n grows large, the shape of the discrete distribution converges to the continuous Gaussian curve of the normal distribution. 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 ...
De Moivre–Laplace theorem; Lyapunov's central limit theorem; Misconceptions about the normal distribution; Martingale central limit theorem; Infinite divisibility (probability) Method of moments (probability theory) Stability (probability) Stein's lemma; Characteristic function (probability theory) Lévy continuity theorem; Darmois ...
This page lists articles related to probability theory.In particular, it lists many articles corresponding to specific probability distributions.Such articles are marked here by a code of the form (X:Y), which refers to number of random variables involved and the type of the distribution.
De Finetti's game; De Finetti's theorem; DeFries–Fulker regression; de Moivre's law; De Moivre–Laplace theorem; Decision boundary; Decision theory; Decomposition of time series; Degenerate distribution; Degrees of freedom (statistics) Delaporte distribution; Delphi method; Delta method; Demand forecasting; Deming regression; Demographics ...
Theorem of de Moivre–Laplace (probability theory) Theorem of the cube (algebraic varieties) Theorem of the gnomon ; Theorem of three moments ; Theorem on friends and strangers (Ramsey theory) Thévenin's theorem (electrical circuits) Thompson transitivity theorem (finite groups) Thompson uniqueness theorem (finite groups)
This approximation, known as de Moivre–Laplace theorem, is a huge time-saver when undertaking calculations by hand (exact calculations with large n are very onerous); historically, it was the first use of the normal distribution, introduced in Abraham de Moivre's book The Doctrine of Chances in 1738.
In probability theory and statistics, the Laplace distribution is a continuous probability distribution named after Pierre-Simon Laplace.It is also sometimes called the double exponential distribution, because it can be thought of as two exponential distributions (with an additional location parameter) spliced together along the abscissa, although the term is also sometimes used to refer to ...
The refinement of Bernoulli's Golden Theorem, regarding the convergence of theoretical probability and empirical probability, was taken up by many notable latter day mathematicians like De Moivre, Laplace, Poisson, Chebyshev, Markov, Borel, Cantelli, Kolmogorov and Khinchin.