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  2. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.

  3. Variance - Wikipedia

    en.wikipedia.org/wiki/Variance

    If the set is a sample from the whole population, then the unbiased sample variance can be calculated as 1017.538 that is the sum of the squared deviations about the mean of the sample, divided by 11 instead of 12. A function VAR.S in Microsoft Excel gives the unbiased sample variance while VAR.P is for population variance.

  4. Variance function - Wikipedia

    en.wikipedia.org/wiki/Variance_function

    In statistics, the variance function is a smooth function that depicts the variance of a random quantity as a function of its mean.The variance function is a measure of heteroscedasticity and plays a large role in many settings of statistical modelling.

  5. Unbiased estimation of standard deviation - Wikipedia

    en.wikipedia.org/wiki/Unbiased_estimation_of...

    Since the square root is a strictly concave function, it follows from Jensen's inequality that the square root of the sample variance is an underestimate. The use of n − 1 instead of n in the formula for the sample variance is known as Bessel's correction , which corrects the bias in the estimation of the population variance, and some, but ...

  6. 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 ...

  7. Tweedie distribution - Wikipedia

    en.wikipedia.org/wiki/Tweedie_distribution

    The variance function V(μ) is constructed from the mean value mapping, = ′ [()]. Here the minus exponent in τ −1 (μ) denotes an inverse function rather than a reciprocal. The mean and variance of an additive random variable is then E(Z) = λμ and var(Z) = λV(μ).

  8. Volume fraction - Wikipedia

    en.wikipedia.org/wiki/Volume_fraction

    It is the same concept as volume percent (vol%) except that the latter is expressed with a denominator of 100, e.g., 18%. The volume fraction coincides with the volume concentration in ideal solutions where the volumes of the constituents are additive (the volume of the solution is equal to the sum of the volumes of its ingredients).

  9. Variogram - Wikipedia

    en.wikipedia.org/wiki/Variogram

    A function is a semivariogram if and only if it is a conditionally negative definite function, i.e. for all weights , …, subject to = = and locations , …, it holds: ∑ i = 1 N ∑ j = 1 N w i γ ( s i , s j ) w j ≤ 0 {\displaystyle \sum _{i=1}^{N}\sum _{j=1}^{N}w_{i}\gamma (\mathbf {s} _{i},\mathbf {s} _{j})w_{j}\leq 0}