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In elementary algebra, the binomial theorem (or binomial expansion) describes the algebraic expansion of powers of a binomial.According to the theorem, the power (+) expands into a polynomial with terms of the form , where the exponents and are nonnegative integers satisfying + = and the coefficient of each term is a specific positive integer ...
The multiplicative formula allows the definition of binomial coefficients to be extended [4] by replacing n by an arbitrary number α (negative, real, complex) or even an element of any commutative ring in which all positive integers are invertible: = _! = () (+) ().
A derivation of Faulhaber's formula using the umbral form is available in The Book of Numbers by John Horton Conway and Richard K. Guy. [17] Classically, this umbral form was considered as a notational convenience. In the modern umbral calculus, on the other hand, this is given a formal mathematical underpinning.
Relationship to the binomial theorem [ edit ] The Leibniz rule bears a strong resemblance to the binomial theorem , and in fact the binomial theorem can be proven directly from the Leibniz rule by taking f ( x ) = e a x {\displaystyle f(x)=e^{ax}} and g ( x ) = e b x , {\displaystyle g(x)=e^{bx},} which gives
The main reason for studying these numbers is to obtain their factorizations.Aside from algebraic factors, which are obtained by factoring the underlying polynomial (binomial) that was used to define the number, such as difference of two squares and sum of two cubes, there are other prime factors (called primitive prime factors, because for a given they do not factorize with <, except for a ...
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Beta negative binomial distribution; Bhargava factorial; Binomial (polynomial) Binomial approximation; Binomial coefficient; Binomial distribution; Binomial regression; Binomial series; Binomial theorem; Binomial transform; Binomial type; Brocard's problem
Different texts (and even different parts of this article) adopt slightly different definitions for the negative binomial distribution. They can be distinguished by whether the support starts at k = 0 or at k = r, whether p denotes the probability of a success or of a failure, and whether r represents success or failure, [1] so identifying the specific parametrization used is crucial in any ...