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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 ...
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. See also. Continuity correction
Sample size determination or estimation is the act of choosing the number of observations or replicates to include in a statistical sample. The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined ...
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 by aggregating the ...
Dunnett's test's calculation is a procedure that is based on calculating confidence statements about the true or the expected values of the differences , thus the differences between treatment groups' mean and control group's mean. This procedure ensures that the probability of all statements being simultaneously correct is equal to a specified ...
Download as PDF; Printable version; ... (1971) provide a correction and equation for this ... the reference gives the exact formulas for any sample size, and can be ...
Gy's sampling theory. Gy's sampling theory is a theory about the sampling of materials, developed by Pierre Gy from the 1950s to beginning 2000s [1] in articles and books including: (1960) Sampling nomogram. (1979) Sampling of particulate materials; theory and practice. (1982) Sampling of particulate materials; theory and practice; 2nd edition.
In survey methodology, the design effect (generally denoted as , , or ) is a measure of the expected impact of a sampling design on the variance of an estimator for some parameter of a population. It is calculated as the ratio of the variance of an estimator based on a sample from an (often) complex sampling design, to the variance of an ...
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