In probability theory, *the* **central limit theorem** (**CLT**) states that, given certain conditions, the mean of a sufficiently large number of independent random variables, each with finite mean and variance, will be approximately normally distributed. The central limit theorem has a number of variants. In its common form, the random variables must be identically distributed. In variants, convergence of the mean to the normal distribution also occurs for non-identical distributions, given that they comply with certain conditions.

In more general probability theory, a **central limit theorem** is any of a set of weak-convergence theories. They all express the fact that a sum of many independent and identically distributed (i.i.d.) random variables, or alternatively, random variables with specific types of dependence, will tend to be distributed according to one of a small set of *attractor distributions*. When the variance of the i.i.d. variables is finite, the attractor distribution is the normal distribution. In contrast, the sum of a number of i.i.d. random variables with power law tail distributions decreasing as |*x*|−α−1 where 0 < α < 2 (and therefore having infinite variance) will tend to an alpha-stable distribution with stability parameter (or index of stability) of α as the number of variables grows.

Read more about Central Limit Theorem: Beyond The Classical Framework, History

### Other articles related to "central limit theorem, theorem":

... of instances may be quickly solved in an approximate way via the

**central limit theorem**in terms of confidence interval around a Gaussian distribution – that's the benefit ... The drawback is that the

**central limit theorem**is applicable when the sample size is sufficiently large ... the burning of a part of sample points, so that the effective sample size to be considered in the

**central limit theorem**is too small ...

**Central Limit Theorem**

... In probability theory, the

**central limit theorem**says that, under certain conditions, the sum of many independent identically-distributed random variables ... The martingale

**central limit theorem**generalizes this result for random variables to martingales, which are stochastic processes where the change in the value of the process from time t to time t + 1 has ...

**Central Limit Theorem**- History

... Tijms writes The

**central limit theorem**has an interesting history ... The first version of this

**theorem**was postulated by the French-born mathematician Abraham de Moivre who, in a remarkable article published in 1733, used the ... It was not until the nineteenth century was at an end that the importance of the

**central limit theorem**was discerned, when, in 1901, Russian ...

...

**Central limit theorem**/ (LR) Berry–Esseen

**theorem**/ (FR) Characteristic function / anl (1FDCR) De Moivre–Laplace

**theorem**/ (LBD) Helly–Bray

**theorem**/ anl (LR) Illustration of the ...

### Famous quotes containing the words theorem, central and/or limit:

“To insure the adoration of a *theorem* for any length of time, faith is not enough, a police force is needed as well.”

—Albert Camus (1913–1960)

“There has never been in history another such culture as the Western civilization M a culture which has practiced the belief that the physical and social environment of man is subject to rational manipulation and that history is subject to the will and action of man; whereas *central* to the traditional cultures of the rivals of Western civilization, those of Africa and Asia, is a belief that it is environment that dominates man.”

—Ishmael Reed (b. 1938)

“We live in oppressive times. We have, as a nation, become our own thought police; but instead of calling the process by which we *limit* our expression of dissent and wonder “censorship,” we call it “concern for commercial viability.””

—David Mamet (b. 1947)