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  2. Central limit theorem - Wikipedia

    en.wikipedia.org/wiki/Central_limit_theorem

    The occurrence of the Gaussian probability density 1 = e −x 2 in repeated experiments, in errors of measurements, which result in the combination of very many and very small elementary errors, in diffusion processes etc., can be explained, as is well-known, by the very same limit theorem, which plays a central role in the calculus of probability.

  3. Stable distribution - Wikipedia

    en.wikipedia.org/wiki/Stable_distribution

    The Generalized Central Limit Theorem (GCLT) was an effort of multiple mathematicians (Berstein, Lindeberg, Lévy, Feller, Kolmogorov, and others) over the period from 1920 to 1937. [14] The first published complete proof (in French) of the GCLT was in 1937 by Paul Lévy. [15]

  4. Convergence of random variables - Wikipedia

    en.wikipedia.org/wiki/Convergence_of_random...

    Then according to the central limit theorem, the distribution of Z n approaches the normal N(0, ⁠ 1 / 3 ⁠) distribution. This convergence is shown in the picture: as n grows larger, the shape of the probability density function gets closer and closer to the Gaussian curve.

  5. Characteristic function (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Characteristic_function...

    Because of the continuity theorem, characteristic functions are used in the most frequently seen proof of the central limit theorem. The main technique involved in making calculations with a characteristic function is recognizing the function as the characteristic function of a particular distribution.

  6. Illustration of the central limit theorem - Wikipedia

    en.wikipedia.org/wiki/Illustration_of_the...

    In probability theory, the central limit theorem (CLT) states that, in many situations, when independent and identically distributed random variables are added, their properly normalized sum tends toward a normal distribution. This article gives two illustrations of this theorem.

  7. Random walk - Wikipedia

    en.wikipedia.org/wiki/Random_walk

    The central limit theorem and the law of the iterated logarithm describe important aspects of the behavior of simple random walks on . In particular, the former entails that as n increases, the probabilities (proportional to the numbers in each row) approach a normal distribution.

  8. Lindeberg's condition - Wikipedia

    en.wikipedia.org/wiki/Lindeberg's_condition

    In probability theory, Lindeberg's condition is a sufficient condition (and under certain conditions also a necessary condition) for the central limit theorem (CLT) to hold for a sequence of independent random variables.

  9. Galton board - Wikipedia

    en.wikipedia.org/wiki/Galton_board

    Galton box A Galton box demonstrated. The Galton board, also known as the Galton box or quincunx or bean machine (or incorrectly Dalton board), is a device invented by Francis Galton [1] to demonstrate the central limit theorem, in particular that with sufficient sample size the binomial distribution approximates a normal distribution.