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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. Power (statistics) - Wikipedia

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

    Post-hoc analysis of "observed power" is conducted after a study has been completed, and uses the obtained sample size and effect size to determine what the power was in the study, assuming the effect size in the sample is equal to the effect size in the population. Whereas the utility of prospective power analysis in experimental design is ...

  4. PS Power and Sample Size - Wikipedia

    en.wikipedia.org/wiki/PS_Power_and_Sample_Size

    Power, sample size, and the detectable alternative hypothesis are interrelated. The user specifies any two of these three quantities and the program derives the third. A description of each calculation, written in English, is generated and may be copied into the user's documents.

  5. G*Power - Wikipedia

    en.wikipedia.org/wiki/G*Power

    A priori analyses are one of the most commonly used analyses in research and calculate the needed sample size in order to achieve a sufficient power level and requires inputted values for alpha and effect size. Compromise analyses find implied power based on the beta/alpha ratio, or q, and inputted values for effect size and sample size ...

  6. Sampling (statistics) - Wikipedia

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

    Formulas, tables, and power function charts are well known approaches to determine sample size. Steps for using sample size tables: Postulate the effect size of interest, α, and β. Check sample size table [20] Select the table corresponding to the selected α; Locate the row corresponding to the desired power; Locate the column corresponding ...

  7. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Set up two statistical hypotheses, H1 and H2, and decide about α, β, and sample size before the experiment, based on subjective cost-benefit considerations. These define a rejection region for each hypothesis. 2 Report the exact level of significance (e.g. p = 0.051 or p = 0.049). Do not refer to "accepting" or "rejecting" hypotheses.

  8. 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.

  9. 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 ...