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  2. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    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 ...

  3. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    The bias decreases as sample size grows, dropping off as 1/N, and thus is most significant for small or moderate sample sizes; for > the bias is below 1%. Thus for very large sample sizes, the uncorrected sample standard deviation is generally acceptable.

  4. Coefficient of variation - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_variation

    The data set [1, 5, 6, 8, 10, 40, 65, 88] has a population standard deviation of 30.8 and a coefficient of variation of 30.8 / 27.9 = 1.10 Estimation [ edit ] When only a sample of data from a population is available, the population CV can be estimated using the ratio of the sample standard deviation s {\displaystyle s\,} to the sample mean x ...

  5. Sampling distribution - Wikipedia

    en.wikipedia.org/wiki/Sampling_distribution

    In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic.If an arbitrarily large number of samples, each involving multiple observations (data points), were separately used in order to compute one value of a statistic (such as, for example, the sample mean or sample variance) for each sample, then the sampling ...

  6. Prediction interval - Wikipedia

    en.wikipedia.org/wiki/Prediction_interval

    Introduction. If one makes the parametric assumption that the underlying distribution is a normal distribution, and has a sample set {X 1, ..., X n}, then confidence intervals and credible intervals may be used to estimate the population mean μ and population standard deviation σ of the underlying population, while prediction intervals may be used to estimate the value of the next sample ...

  7. Power of a test - Wikipedia

    en.wikipedia.org/wiki/Power_of_a_test

    Power of a test. In statistics, the power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis ( ) when the alternative hypothesis ( ) is true. It is commonly denoted by , and represents the probability of a true positive detection of an effect or an association between variables, conditional on the ...

  8. Confidence interval - Wikipedia

    en.wikipedia.org/wiki/Confidence_interval

    A confidence interval for the parameter , with confidence level or coefficient , is an interval determined by random variables and with the property: The number , whose typical value is close to but not greater than 1, is sometimes given in the form (or as a percentage ), where is a small positive number, often 0.05.

  9. Shapiro–Wilk test - Wikipedia

    en.wikipedia.org/wiki/Shapiro–Wilk_test

    The Shapiro–Wilk test tests the null hypothesis that a sample x1, ..., xn came from a normally distributed population. The test statistic is. where. with parentheses enclosing the subscript index i is the i th order statistic, i.e., the i th-smallest number in the sample (not to be confused with ). is the sample mean.

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