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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. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    Consider a concrete example, such as the global surface temperature record of the past 140 years as presented by the IPCC. [3] The interannual variation is about 0.2 °C, and the trend is about 0.6 °C over 140 years, with 95% confidence limits of 0.2 °C (by coincidence, about the same value as the interannual variation). Hence, the trend is ...

  4. 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.

  5. Variance function - Wikipedia

    en.wikipedia.org/wiki/Variance_function

    When a member of the exponential family has been specified, the variance function can easily be derived. [4]: 29 The general form of the variance function is presented under the exponential family context, as well as specific forms for Normal, Bernoulli, Poisson, and Gamma. In addition, we describe the applications and use of variance functions ...

  6. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    GPR is a Bayesian non-linear regression method. A Gaussian process (GP) is a collection of random variables, any finite number of which have a joint Gaussian (normal) distribution. A GP is defined by a mean function and a covariance function, which specify the mean vectors and covariance matrices for each finite collection of the random variables.

  7. Explained variation - Wikipedia

    en.wikipedia.org/wiki/Explained_variation

    Often, variation is quantified as variance; then, the more specific term explained variance can be used. The complementary part of the total variation is called unexplained or residual variation ; likewise, when discussing variance as such, this is referred to as unexplained or residual variance .

  8. Ratio estimator - Wikipedia

    en.wikipedia.org/wiki/Ratio_estimator

    The variance of the sample ratio is approximately: ... The sample estimate was 71,866.333 baptisms per year over this period giving a ratio of one registered baptism ...

  9. Coefficient of variation - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_variation

    This follows from the fact that the variance and mean are independent of the ordering of x. Scale invariance: c v (x) = c v (αx) where α is a real number. [22] Population independence – If {x,x} is the list x appended to itself, then c v ({x,x}) = c v (x). This follows from the fact that the variance and mean both obey this principle.