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  2. Central limit theorem - Wikipedia

    en.wikipedia.org/wiki/Central_limit_theorem

    A curious footnote to the history of the Central Limit Theorem is that a proof of a result similar to the 1922 Lindeberg CLT was the subject of Alan Turing's 1934 Fellowship Dissertation for King's College at the University of Cambridge. Only after submitting the work did Turing learn it had already been proved.

  3. Lindeberg's condition - Wikipedia

    en.wikipedia.org/wiki/Lindeberg's_condition

    This theorem can be used to disprove the central limit theorem holds for by using proof by contradiction. This procedure involves proving that Lindeberg's condition fails for X k {\displaystyle X_{k}} .

  4. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    Comparison of probability density functions, () for the sum of fair 6-sided dice to show their convergence to a normal distribution with increasing , in accordance to the central limit theorem. In the bottom-right graph, smoothed profiles of the previous graphs are rescaled, superimposed and compared with a normal distribution (black curve).

  5. Category:Central limit theorem - Wikipedia

    en.wikipedia.org/wiki/Category:Central_limit_theorem

    This page was last edited on 1 December 2024, at 08:30 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.

  6. Illustration of the central limit theorem - Wikipedia

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

    This section illustrates the central limit theorem via an example for which the computation can be done quickly by hand on paper, unlike the more computing-intensive example of the previous section. Sum of all permutations of length 1 selected from the set of integers 1, 2, 3

  7. Jarl Waldemar Lindeberg - Wikipedia

    en.wikipedia.org/wiki/Jarl_Waldemar_Lindeberg

    In 1920 he published his first paper on the central limit theorem. His result was similar to that obtained earlier by Lyapunov whose work he did not then know. However, their approaches were quite different; Lindeberg's was based on a convolution argument while Lyapunov used the characteristic function .

  8. Asymptotic distribution - Wikipedia

    en.wikipedia.org/wiki/Asymptotic_distribution

    The central limit theorem gives only an asymptotic distribution. As an approximation for a finite number of observations, it provides a reasonable approximation only when close to the peak of the normal distribution; it requires a very large number of observations to stretch into the tails.

  9. List of theorems - Wikipedia

    en.wikipedia.org/wiki/List_of_theorems

    Cayley's theorem (group theory) Central limit theorem (probability) Cesàro's theorem (real analysis) Ceva's theorem ; Chasles's theorems; Chebotarev's density theorem (number theory) Chen's theorem (number theory) Cheng's eigenvalue comparison theorem (Riemannian geometry) Chern–Gauss–Bonnet theorem (differential geometry)

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