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  2. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    The above image shows a table with some of the most common test statistics and their corresponding tests or models. A statistical hypothesis test is a method of statistical inference used to decide whether the data sufficiently supports a particular hypothesis. A statistical hypothesis test typically involves a calculation of a test statistic.

  3. 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.

  4. List of statistical tests - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_tests

    Statistical tests are used to test the fit between a hypothesis and the data. [1] [2] Choosing the right statistical test is not a trivial task. [1]The choice of the test depends on many properties of the research question.

  5. Exact statistics - Wikipedia

    en.wikipedia.org/wiki/Exact_statistics

    Exact statistics, such as that described in exact test, is a branch of statistics that was developed to provide more accurate results pertaining to statistical testing and interval estimation by eliminating procedures based on asymptotic and approximate statistical methods.

  6. Power (statistics) - Wikipedia

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

    Illustration of the power of a statistical test, for a two sided test, through the probability distribution of the test statistic under the null and alternative hypothesis. α is shown as the blue area, the probability of rejection under null, while the red area shows power, 1 − β, the probability of correctly rejecting under the alternative.

  7. Exact test - Wikipedia

    en.wikipedia.org/wiki/Exact_test

    However, in practice, most implementations of non-parametric test software use asymptotical algorithms to obtain the significance value, which renders the test non-exact. Hence, when a result of statistical analysis is termed an “exact test” or specifies an “exact p-value ”, this implies that the test is defined without parametric ...

  8. Fisher's exact test - Wikipedia

    en.wikipedia.org/wiki/Fisher's_exact_test

    Furthermore, Boschloo's test is an exact test that is uniformly more powerful than Fisher's exact test by construction. [25] Most modern statistical packages will calculate the significance of Fisher tests, in some cases even where the chi-squared approximation would also be acceptable. The actual computations as performed by statistical ...

  9. Pearson's chi-squared test - Wikipedia

    en.wikipedia.org/wiki/Pearson's_chi-squared_test

    Pearson's chi-squared test or Pearson's test is a statistical test applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets arose by chance. It is the most widely used of many chi-squared tests (e.g., Yates , likelihood ratio , portmanteau test in time series , etc.) – statistical ...