Search results
Results from the WOW.Com Content Network
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.
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}} .
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.
Campbell's theorem (probability) Central limit theorem; Characterization of probability distributions; Chung–Erdős inequality; Condorcet's jury theorem; Continuous mapping theorem; Contraction principle (large deviations theory) Coupon collector's problem; Cox's theorem; Cramér–Wold theorem; Cramér's theorem (large deviations) Cramér's ...
2 Proof. 3 References. ... Download as PDF; Printable version ... This theorem is the basis for one approach to prove the central limit theorem and is one of the ...
The law of iterated logarithms operates "in between" the law of large numbers and the central limit theorem.There are two versions of the law of large numbers — the weak and the strong — and they both state that the sums S n, scaled by n −1, converge to zero, respectively in probability and almost surely:
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
The central limit theorem can provide more detailed information about the behavior of than the law of large numbers. For example, we can approximately find a tail probability of M N {\displaystyle M_{N}} – the probability that M N {\displaystyle M_{N}} is greater than some value x {\displaystyle x} – for a fixed value of N {\displaystyle N} .