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  2. Order of operations - Wikipedia

    en.wikipedia.org/wiki/Order_of_operations

    In mathematics and computer programming, the order of operations is a collection of rules that reflect conventions about which operations to perform first in order to evaluate a given mathematical expression. These rules are formalized with a ranking of the operations.

  3. Scott's rule - Wikipedia

    en.wikipedia.org/wiki/Scott's_Rule

    Scott's rule is a method to select the number of bins in a histogram. [1] Scott's rule is widely employed in data analysis software including R, [2] Python [3] and Microsoft Excel where it is the default bin selection method. [4]

  4. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    Excel maintains 15 figures in its numbers, but they are not always accurate; mathematically, the bottom line should be the same as the top line, in 'fp-math' the step '1 + 1/9000' leads to a rounding up as the first bit of the 14 bit tail '10111000110010' of the mantissa falling off the table when adding 1 is a '1', this up-rounding is not undone when subtracting the 1 again, since there is no ...

  5. Gauss–Kronrod quadrature formula - Wikipedia

    en.wikipedia.org/wiki/Gauss–Kronrod_quadrature...

    Gauss–Kronrod formulas are extensions of the Gauss quadrature formulas generated by adding + points to an -point rule in such a way that the resulting rule is exact for polynomials of degree less than or equal to + (Laurie (1997, p. 1133); the corresponding Gauss rule is of order ).

  6. Sturges's rule - Wikipedia

    en.wikipedia.org/wiki/Sturges's_rule

    This rule is widely employed in data analysis software including Python [2] and R, where it is the default bin selection method. [3] Sturges's rule comes from the binomial distribution which is used as a discrete approximation to the normal distribution. [4] If the function to be approximated is binomially distributed then

  7. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables ⁡ (+) = ⁡ + ⁡ + ⁡ (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...

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  9. Sum of normally distributed random variables - Wikipedia

    en.wikipedia.org/wiki/Sum_of_normally...

    The characteristic function + = ⁡ ((+)) of the sum of two independent random variables X and Y is just the product of the two separate characteristic functions: = ⁡ (), = ⁡ ()