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  2. 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 .

  3. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    An example of Neyman–Pearson hypothesis testing (or null hypothesis statistical significance testing) can be made by a change to the radioactive suitcase example. If the "suitcase" is actually a shielded container for the transportation of radioactive material, then a test might be used to select among three hypotheses: no radioactive source ...

  4. Likelihood-ratio test - Wikipedia

    en.wikipedia.org/wiki/Likelihood-ratio_test

    The likelihood-ratio test, also known as Wilks test, [2] is the oldest of the three classical approaches to hypothesis testing, together with the Lagrange multiplier test and the Wald test. [3] In fact, the latter two can be conceptualized as approximations to the likelihood-ratio test, and are asymptotically equivalent.

  5. Hypothetico-deductive model - Wikipedia

    en.wikipedia.org/wiki/Hypothetico-deductive_model

    investigations that do or do not provide a potentially falsifying test of the hypothesis. [7] Evidence contrary to a hypothesis is itself philosophically problematic. Such evidence is called a falsification of the hypothesis. However, under the theory of confirmation holism it is always possible to save a given hypothesis from falsification ...

  6. Statistical significance - Wikipedia

    en.wikipedia.org/wiki/Statistical_significance

    Starting in the 2010s, some journals began questioning whether significance testing, and particularly using a threshold of α =5%, was being relied on too heavily as the primary measure of validity of a hypothesis. [52] Some journals encouraged authors to do more detailed analysis than just a statistical significance test.

  7. Power (statistics) - Wikipedia

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

    Under a frequentist hypothesis testing framework, this is done by calculating a test statistic (such as a t-statistic) for the dataset, which has a known theoretical probability distribution if there is no difference (the so called null hypothesis). If the actual value calculated on the sample is sufficiently unlikely to arise under the null ...

  8. Hypothesis - Wikipedia

    en.wikipedia.org/wiki/Hypothesis

    The hypothesis of Andreas Cellarius, showing the planetary motions in eccentric and epicyclical orbits. A hypothesis (pl.: hypotheses) is a proposed explanation for a phenomenon. A scientific hypothesis must be based on observations and make a testable and reproducible prediction about reality, in a process beginning with an educated guess or ...

  9. Null hypothesis - Wikipedia

    en.wikipedia.org/wiki/Null_hypothesis

    A statistical significance test starts with a random sample from a population. If the sample data are consistent with the null hypothesis, then you do not reject the null hypothesis; if the sample data are inconsistent with the null hypothesis, then you reject the null hypothesis and conclude that the alternative hypothesis is true. [3]