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  2. Sign test - Wikipedia

    en.wikipedia.org/wiki/Sign_test

    The sign test is a special case of the binomial test where the probability of success under the null hypothesis is p=0.5. Thus, the sign test can be performed using the binomial test, which is provided in most statistical software programs. On-line calculators for the sign test can be founded by searching for "sign test calculator".

  3. Null hypothesis - Wikipedia

    en.wikipedia.org/wiki/Null_hypothesis

    Therefore, the two-tailed null hypothesis will be preserved in this case, not supporting the conclusion reached with the single-tailed null hypothesis, that the coin is biased towards heads. This example illustrates that the conclusion reached from a statistical test may depend on the precise formulation of the null and alternative hypotheses.

  4. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Region of rejection / Critical region: The set of values of the test statistic for which the null hypothesis is rejected. Power of a test (1 − β) Size: For simple hypotheses, this is the test's probability of incorrectly rejecting the null hypothesis. The false positive rate. For composite hypotheses this is the supremum of the probability ...

  5. Wilcoxon signed-rank test - Wikipedia

    en.wikipedia.org/wiki/Wilcoxon_signed-rank_test

    The Wilcoxon signed-rank test is a non-parametric rank test for statistical hypothesis testing used either to test the location of a population based on a sample of data, or to compare the locations of two populations using two matched samples. [1] The one-sample version serves a purpose similar to that of the one-sample Student's t-test. [2]

  6. Type I and type II errors - Wikipedia

    en.wikipedia.org/wiki/Type_I_and_type_II_errors

    This is why the hypothesis under test is often called the null hypothesis (most likely, coined by Fisher (1935, p. 19)), because it is this hypothesis that is to be either nullified or not nullified by the test. When the null hypothesis is nullified, it is possible to conclude that data support the "alternative hypothesis" (which is the ...

  7. Statistical significance - Wikipedia

    en.wikipedia.org/wiki/Statistical_significance

    A two-tailed test may still be used but it will be less powerful than a one-tailed test, because the rejection region for a one-tailed test is concentrated on one end of the null distribution and is twice the size (5% vs. 2.5%) of each rejection region for a two-tailed test. As a result, the null hypothesis can be rejected with a less extreme ...

  8. One- and two-tailed tests - Wikipedia

    en.wikipedia.org/wiki/One-_and_two-tailed_tests

    A two-tailed test applied to the normal distribution. A one-tailed test, showing the p-value as the size of one tail. In statistical significance testing, a one-tailed test and a two-tailed test are alternative ways of computing the statistical significance of a parameter inferred from a data set, in terms of a test statistic. A two-tailed test ...

  9. Null distribution - Wikipedia

    en.wikipedia.org/wiki/Null_distribution

    In statistical hypothesis testing, the null distribution is the probability distribution of the test statistic when the null hypothesis is true. [1] For example, in an F-test, the null distribution is an F-distribution. [2] Null distribution is a tool scientists often use when conducting experiments.