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  2. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]

  3. Margin of error - Wikipedia

    en.wikipedia.org/wiki/Margin_of_error

    For a confidence level, there is a corresponding confidence interval about the mean , that is, the interval [, +] within which values of should fall with probability . ...

  4. Cohen's h - Wikipedia

    en.wikipedia.org/wiki/Cohen's_h

    It can be used in calculating the sample size for a future study. When measuring differences between proportions, Cohen's h can be used in conjunction with hypothesis testing . A " statistically significant " difference between two proportions is understood to mean that, given the data, it is likely that there is a difference in the population ...

  5. Confidence region - Wikipedia

    en.wikipedia.org/wiki/Confidence_region

    The confidence region is calculated in such a way that if a set of measurements were repeated many times and a confidence region calculated in the same way on each set of measurements, then a certain percentage of the time (e.g. 95%) the confidence region would include the point representing the "true" values of the set of variables being estimated.

  6. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    Mathematically, the variance of the sampling mean distribution obtained is equal to the variance of the population divided by the sample size. This is because as the sample size increases, sample means cluster more closely around the population mean.

  7. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    The sample mean could serve as a good estimator of the population mean. Then we have: The difference between the height of each man in the sample and the unobservable population mean is a statistical error, whereas; The difference between the height of each man in the sample and the observable sample mean is a residual.

  8. Sampling error - Wikipedia

    en.wikipedia.org/wiki/Sampling_error

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  9. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    If the sample size is 1,000, then the effective sample size will be 500. It means that the variance of the weighted mean based on 1,000 samples will be the same as that of a simple mean based on 500 samples obtained using a simple random sample.