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  2. Statistical proof - Wikipedia

    en.wikipedia.org/wiki/Statistical_proof

    Statistical proof is the rational demonstration of degree of certainty for a proposition, hypothesis or theory that is used to convince others subsequent to a statistical test of the supporting evidence and the types of inferences that can be drawn from the test scores.

  3. 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).

  4. List of statistics articles - Wikipedia

    en.wikipedia.org/wiki/List_of_statistics_articles

    Download as PDF; Printable version; In other projects ... Statistical sample; ... Stein's example. Proof of Stein's example;

  5. Closed testing procedure - Wikipedia

    en.wikipedia.org/wiki/Closed_testing_procedure

    2 Example. 3 Special cases. ... Download as PDF; Printable version; In other projects ... In statistics, the closed testing procedure [1] ...

  6. Proof procedure - Wikipedia

    en.wikipedia.org/wiki/Proof_procedure

    A proof procedure for a logic is complete if it produces a proof for each provable statement. The theorems of logical systems are typically recursively enumerable, which implies the existence of a complete but usually extremely inefficient proof procedure; however, a proof procedure is only of interest if it is reasonably efficient.

  7. Permutation test - Wikipedia

    en.wikipedia.org/wiki/Permutation_test

    A permutation test (also called re-randomization test or shuffle test) is an exact statistical hypothesis test making use of the proof by contradiction. A permutation test involves two or more samples. The null hypothesis is that all samples come from the same distribution : =.

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  9. Bartlett's test - Wikipedia

    en.wikipedia.org/wiki/Bartlett's_test

    This test procedure is based on the statistic whose sampling distribution is approximately a Chi-Square distribution with (k − 1) degrees of freedom, where k is the number of random samples, which may vary in size and are each drawn from independent normal distributions. Bartlett's test is sensitive to departures from normality.