Übersetzung für "Central limit theorem" in Deutsch

The Central Limit Theorem leads to approximations for discrete distributions.

He proved the central limit theorem under fairly general assumptions.

The importance of the normal distribution in statistics is caused by the central limit theorem .

This trick is based on the consequences of the central limit theorem.

This is an instance of the Central Limit Theorem.

But the rigorous proof of the Central Limit Theorem came from the Russian mathematicians.

The Central Limit Theorem (CLT) is a powerful and important result of mathematical analysis.

Inspired by the harmonic-analytic research of Harald Cramér and Arne Beurling, Esseen examined the accuracy of the approximation to the normal distribution in the central limit theorem in the case of independent and identically distributed summands.

Markov and Lyapunov are today usually called as representatives of the St. Petersburg School (founded by Pafnuty Chebyshev) when it comes to the question of the first mathematically strict treatment of the Central Limit Theorem, the discussion and debate with Nekrasov played a significant role (especially one essay from 1898).

This formula for the variance of the mean is used in the definition of the standard error of the sample mean, which is used in the central limit theorem.

Although Esseen worked mostly on the central limit theorem and related topics, he also worked in other areas.

The mathematical problem appears to date from 1888 where Edgeworth used the central limit theorem to determine the optimal cash reserves to satisfy random withdrawals from depositors.

Although the central limit theorem had recently been discovered, Turing was not aware of this and discovered it independently.

Note that a normal distribution can be approximated from a uniform distribution by applying the central limit theorem.

The Central Limit Theorem then implies that dz has a normal distribution and hence is completely characterized by its mean and standard deviation.

In smooth ergodic theory, one considers the behavior of typical (in terms of an invariant measure) evolutions in order to make statistical statements, such as rates of mixing and the central limit theorem.

Chebyshev started the project to obtain a rigorous development of the Central Limit Theorem and his students, Andrei A. Markov and Alexander M. Lyapunov.

In particular in two papers published in 1900 and 1901, he proved the central limit theorem using a technique based on characteristic functions.

He wrote on the normal distribution and coined the term "central limit theorem" in 1920 which is now standard usage.

It was Lyapunov's analysis that led to the modern characteristic function approach to the Central Limit Theorem.

The mathematician and politician Pierre Laplace had already proved the central limit theorem, which provides the foundation for the theoretical importance of the normal distribution.

Turing was elected a fellow of King's College, Cambridge, in 1935 for a dissertation On the Gaussian error function which proved fundamental results on probability theory, namely the central limit theorem .

We should give two specific results which we have not mentioned previously which will be remembered as major contributions, namely his work on the central limit theorem and his beautiful theorem that if the sum of two independent random variables is normal then all are normal.