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  2. Stirling's approximation - Wikipedia

    en.wikipedia.org/wiki/Stirling's_approximation

    Now the function + is unimodal, with maximum value zero. Locally around zero, it looks like − t 2 / 2 {\displaystyle -t^{2}/2} , which is why we are able to perform Laplace's method. In order to extend Laplace's method to higher orders, we perform another change of variables by 1 + t − e t = − τ 2 / 2 {\displaystyle 1+t-e^{t}=-\tau ^{2}/2} .

  3. Empty product - Wikipedia

    en.wikipedia.org/wiki/Empty_product

    For example, the empty products 0! = 1 (the factorial of zero) and x 0 = 1 shorten Taylor series notation (see zero to the power of zero for a discussion of when x = 0). Likewise, if M is an n × n matrix, then M 0 is the n × n identity matrix , reflecting the fact that applying a linear map zero times has the same effect as applying the ...

  4. Factorial - Wikipedia

    en.wikipedia.org/wiki/Factorial

    The special case of Legendre's formula for = gives the number of trailing zeros in the decimal representation of the factorials. [57] According to this formula, the number of zeros can be obtained by subtracting the base-5 digits of from , and dividing the result by four. [58]

  5. Googol - Wikipedia

    en.wikipedia.org/wiki/Googol

    A googol is the large number 10 100 or ten to the power of one hundred. In decimal notation, it is written as the digit 1 followed by one hundred zeros: 10, 000, 000 ...

  6. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    In numerical analysis, a root-finding algorithm is an algorithm for finding zeros, also called "roots", of continuous functions. A zero of a function f is a number x such that f(x) = 0. As, generally, the zeros of a function cannot be computed exactly nor expressed in closed form, root-finding algorithms provide approximations to zeros.

  7. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

    x erf x 1 − erf x; 0: 0: 1: 0.02: 0.022 564 575: 0.977 435 425: 0.04: 0.045 111 106: 0.954 888 894: 0.06: 0.067 621 594: 0.932 378 406: 0.08: 0.090 078 126: 0.909 ...

  8. Lyft shares rocket 62% over a typo in the company's earnings ...

    www.aol.com/news/one-too-many-zeros-lyft...

    However, the company informed investors about five minutes after the original release that there was one zero too many in that number and corrected it to 50 basis points, a much more realistic 0.5%.

  9. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    This rounding rule is biased because it always moves the result toward zero. Round-to-nearest: () is set to the nearest floating-point number to . When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal to 0) is used.