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  2. Power (statistics) - Wikipedia

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

    We define two hypotheses the null hypothesis, and the alternative hypothesis. If we design the test such that α is the significance level - being the probability of rejecting when is in fact true, then the power of the test is 1 - β where β is the probability of failing to reject when the alternative is true.

  3. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    The modern version of hypothesis testing is a hybrid of the two approaches that resulted from ... for which the null hypothesis is rejected. Power of a test (1 ...

  4. Uniformly most powerful test - Wikipedia

    en.wikipedia.org/wiki/Uniformly_most_powerful_test

    In statistical hypothesis testing, a uniformly most powerful (UMP) test is a hypothesis test which has the greatest power among all possible tests of a given size α. For example, according to the Neyman–Pearson lemma , the likelihood-ratio test is UMP for testing simple (point) hypotheses.

  5. 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 ...

  6. Neyman–Pearson lemma - Wikipedia

    en.wikipedia.org/wiki/Neyman–Pearson_lemma

    Neyman–Pearson lemma [5] — Existence:. If a hypothesis test satisfies condition, then it is a uniformly most powerful (UMP) test in the set of level tests.. Uniqueness: If there exists a hypothesis test that satisfies condition, with >, then every UMP test in the set of level tests satisfies condition with the same .

  7. Sign test - Wikipedia

    en.wikipedia.org/wiki/Sign_test

    The alternative hypothesis is that hind leg length may be either greater than or less than foreleg length, which is a two sided test, specified as alternative="two.sided". The R command binom.test (x = 8, n = 10, p = 0.5, alternative = "two.sided") gives p=0.1094, as in the example.

  8. Equivalence test - Wikipedia

    en.wikipedia.org/wiki/Equivalence_test

    A very simple equivalence testing approach is the ‘two one-sided t-tests’ (TOST) procedure. [11] In the TOST procedure an upper (Δ U) and lower (–Δ L) equivalence bound is specified based on the smallest effect size of interest (e.g., a positive or negative difference of d = 0.3).

  9. Boschloo's test - Wikipedia

    en.wikipedia.org/wiki/Boschloo's_test

    Boschloo's test is a statistical hypothesis test for analysing 2x2 ... The null hypothesis of the two-tailed test is: ... The power of this test is similar to that of ...