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The word "factorial" (originally French: factorielle) was first used in 1800 by Louis François Antoine Arbogast, [18] in the first work on Faà di Bruno's formula, [19] but referring to a more general concept of products of arithmetic progressions. The "factors" that this name refers to are the terms of the product formula for the factorial. [20]
However, the gamma function, unlike the factorial, is more broadly defined for all complex numbers other than non-positive integers; nevertheless, Stirling's formula may still be applied.
The falling factorial occurs in a formula which represents polynomials using the forward difference operator = (+) , which in form is an exact analogue to Taylor's theorem: Compare the series expansion from umbral calculus
The ordinary factorial, when extended to the gamma function, has a pole at each negative integer, preventing the factorial from being defined at these numbers. However, the double factorial of odd numbers may be extended to any negative odd integer argument by inverting its recurrence relation n ! ! = n × ( n − 2 ) ! ! {\displaystyle n!!=n ...
A two-sum formula can be obtained using one of the symmetric formulae for Stirling numbers in conjunction with the explicit formula for Stirling numbers of the second kind. [ n k ] = ∑ j = n 2 n − k ( j − 1 k − 1 ) ( 2 n − k j ) ∑ m = 0 j − n ( − 1 ) m + n − k m j − k m !
Other extensions of the factorial function do exist, but the gamma function is the most popular and useful. It appears as a factor in various probability-distribution functions and other formulas in the fields of probability , statistics , analytic number theory , and combinatorics .
A more efficient method to compute individual binomial coefficients is given by the formula = _! = () (()) () = = +, where the numerator of the first fraction, _, is a falling factorial. This formula is easiest to understand for the combinatorial interpretation of binomial coefficients.
Each generator halves the number of runs required. A design with p such generators is a 1/(l p)=l −p fraction of the full factorial design. [3] For example, a 2 5 − 2 design is 1/4 of a two-level, five-factor factorial design. Rather than the 32 runs that would be required for the full 2 5 factorial experiment, this experiment requires only ...