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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. Cohen's h - Wikipedia

    en.wikipedia.org/wiki/Cohen's_h

    Researchers have used Cohen's h as follows.. Describe the differences in proportions using the rule of thumb criteria set out by Cohen. [1] Namely, h = 0.2 is a "small" difference, h = 0.5 is a "medium" difference, and h = 0.8 is a "large" difference.

  4. Binomial test - Wikipedia

    en.wikipedia.org/wiki/Binomial_test

    A binomial test is a statistical hypothesis test used to determine whether the proportion of successes in a sample differs from an expected proportion in a binomial distribution. It is useful for situations when there are two possible outcomes (e.g., success/failure, yes/no, heads/tails), i.e., where repeated experiments produce binary data .

  5. Application for employment - Wikipedia

    en.wikipedia.org/wiki/Application_for_employment

    The typical application also requires the applicant to provide information regarding relevant skills, education, and experience (previous employment or volunteer work). The application itself is a minor test of the applicant's literacy, penmanship, and communication skills. A careless job applicant might disqualify themselves with a poorly ...

  6. p-chart - Wikipedia

    en.wikipedia.org/wiki/P-chart

    [2]: 277 If the organization elects to only inspect a fraction of units produced, the sample size should be chosen large enough so that the chance of finding at least one nonconforming unit in a sample is high—otherwise the false alarm rate is too high. One technique is to fix sample size so that there is a 50% chance of detecting a process ...

  7. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    Difference between Z-test and t-test: Z-test is used when sample size is large (n>50), or the population variance is known. t-test is used when sample size is small (n<50) and population variance is unknown. There is no universal constant at which the sample size is generally considered large enough to justify use of the plug-in test.

  8. What is the 50/30/20 budget rule? - AOL

    www.aol.com/finance/50-30-20-budget-rule...

    The 50/30/20 rule is a simple budgeting strategy that can eliminate the need to create a detailed budget with precise spending amounts and a dozen or more line items. It also provides a framework ...

  9. 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.