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  2. Bessel's correction - Wikipedia

    en.wikipedia.org/wiki/Bessel's_correction

    Bessel's correction. In statistics, Bessel's correction is the use of n − 1 instead of n in the formula for the sample variance and sample standard deviation, [1] where n is the number of observations in a sample. This method corrects the bias in the estimation of the population variance. It also partially corrects the bias in the estimation ...

  3. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    4.2 Correction for correlation in the sample. 5 See also. ... Download as PDF; ... the reference gives the exact formulas for any sample size, and can be applied to ...

  4. Yates's correction for continuity - Wikipedia

    en.wikipedia.org/wiki/Yates's_correction_for...

    Yates's correction should always be applied, as it will tend to improve the accuracy of the p-value obtained. [ citation needed ] However, in situations with large sample sizes, using the correction will have little effect on the value of the test statistic, and hence the p-value.

  5. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    Where is the sample size, = / is the fraction of the sample from the population, () is the (squared) finite population correction (FPC), is the unbiassed sample variance, and (¯) is some estimator of the variance of the mean under the sampling design. The issue with the above formula is that it is extremely rare to be able to directly estimate ...

  6. Unbiased estimation of standard deviation - Wikipedia

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

    Correction factor versus sample size n.. When the random variable is normally distributed, a minor correction exists to eliminate the bias.To derive the correction, note that for normally distributed X, Cochran's theorem implies that () / has a chi square distribution with degrees of freedom and thus its square root, / has a chi distribution with degrees of freedom.

  7. Jackknife resampling - Wikipedia

    en.wikipedia.org/wiki/Jackknife_resampling

    Jackknife resampling. In statistics, the jackknife (jackknife cross-validation) is a cross-validation technique and, therefore, a form of resampling. It is especially useful for bias and variance estimation. The jackknife pre-dates other common resampling methods such as the bootstrap. Given a sample of size , a jackknife estimator can be built ...

  8. Fisher's exact test - Wikipedia

    en.wikipedia.org/wiki/Fisher's_exact_test

    Fisher's exact test is a statistical significance test used in the analysis of contingency tables. [1][2][3] Although in practice it is employed when sample sizes are small, it is valid for all sample sizes. It is named after its inventor, Ronald Fisher, and is one of a class of exact tests, so called because the significance of the deviation ...

  9. Newey–West estimator - Wikipedia

    en.wikipedia.org/wiki/Newey–West_estimator

    Newey–West estimator. A Newey–West estimator is used in statistics and econometrics to provide an estimate of the covariance matrix of the parameters of a regression-type model where the standard assumptions of regression analysis do not apply. [1] It was devised by Whitney K. Newey and Kenneth D. West in 1987, although there are a number ...