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  2. Bernoulli number - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_number

    In mathematics, the Bernoulli numbers B n are a sequence of rational numbers which occur frequently in analysis.The Bernoulli numbers appear in (and can be defined by) the Taylor series expansions of the tangent and hyperbolic tangent functions, in Faulhaber's formula for the sum of m-th powers of the first n positive integers, in the Euler–Maclaurin formula, and in expressions for certain ...

  3. Binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Binomial_distribution

    A Binomial distributed random variable X ~ B(n, p) can be considered as the sum of n Bernoulli distributed random variables. So the sum of two Binomial distributed random variables X ~ B(n, p) and Y ~ B(m, p) is equivalent to the sum of n + m Bernoulli distributed random variables, which means Z = X + Y ~ B(n + m, p). This can also be proven ...

  4. Bernoulli distribution - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_distribution

    The categorical distribution is the generalization of the Bernoulli distribution for variables with any constant number of discrete values. The Beta distribution is the conjugate prior of the Bernoulli distribution. [5] The geometric distribution models the number of independent and identical Bernoulli trials needed to get one success.

  5. Relationships among probability distributions - Wikipedia

    en.wikipedia.org/wiki/Relationships_among...

    Other distributions are not closed under convolution, but their sum has a known distribution: The sum of n Bernoulli (p) random variables is a binomial (n, p) random variable. The sum of n geometric random variables with probability of success p is a negative binomial random variable with parameters n and p.

  6. Completeness (statistics) - Wikipedia

    en.wikipedia.org/wiki/Completeness_(statistics)

    The Bernoulli model admits a complete statistic. [3] Let X be a random sample of size n such that each X i has the same Bernoulli distribution with parameter p. Let T be the number of 1s observed in the sample, i.e. = =. T is a statistic of X which has a binomial distribution with parameters (n,p).

  7. Faulhaber's formula - Wikipedia

    en.wikipedia.org/wiki/Faulhaber's_formula

    Jakob Bernoulli's Summae Potestatum, Ars Conjectandi, 1713. In 1713, Jacob Bernoulli published under the title Summae Potestatum an expression of the sum of the p powers of the n first integers as a (p + 1)th-degree polynomial function of n, with coefficients involving numbers B j, now called Bernoulli numbers:

  8. Poisson binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Poisson_binomial_distribution

    Since a Poisson binomial distributed variable is a sum of n independent Bernoulli distributed variables, its mean and variance will simply be sums of the mean and variance of the n Bernoulli distributions: = =

  9. Bernoulli process - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_process

    The term Bernoulli sequence is often used informally to refer to a realization of a Bernoulli process. However, the term has an entirely different formal definition as given below. Suppose a Bernoulli process formally defined as a single random variable (see preceding section). For every infinite sequence x of coin flips, there is a sequence of ...