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The regularized incomplete beta function is the cumulative distribution function of the beta distribution, and is related to the cumulative distribution function (;,) of a random variable X following a binomial distribution with probability of single success p and number of Bernoulli trials n:
For every odd positive integer +, the following equation holds: [3] (+) = ()!() +where is the n-th Euler Number.This yields: =,() =,() =,() =For the values of the Dirichlet beta function at even positive integers no elementary closed form is known, and no method has yet been found for determining the arithmetic nature of even beta values (similarly to the Riemann zeta function at odd integers ...
In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1) in terms of two positive parameters, denoted by alpha (α) and beta (β), that appear as exponents of the variable and its complement to 1, respectively, and control the shape of the distribution.
The Dirac delta function, although not strictly a probability distribution, is a limiting form of many continuous probability functions. It represents a discrete probability distribution concentrated at 0 — a degenerate distribution — it is a Distribution (mathematics) in the generalized function sense; but the notation treats it as if it ...
where β is the Dirichlet beta function. Its numerical value [1] is approximately (sequence A006752 in the OEIS) G = 0.915 965 594 177 219 015 054 603 514 932 384 110 774 … Catalan's constant was named after Eugène Charles Catalan, who found quickly-converging series for its calculation and published a memoir on it in 1865. [2] [3]
Perhaps the best-known value of the gamma function at a non-integer argument is =, which can be found by setting = in the reflection or duplication formulas, by using the relation to the beta function given below with = =, or simply by making the substitution = in the integral definition of the gamma function, resulting in a Gaussian integral.
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In creating reference tables for binomial distribution probability, usually, the table is filled in up to n/2 values. This is because for k > n/2, the probability can be calculated by its complement as (,,) = (,,).