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  2. 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 ...

  3. Two-sample hypothesis testing - Wikipedia

    en.wikipedia.org/wiki/Two-sample_hypothesis_testing

    In statistical hypothesis testing, a two-sample test is a test performed on the data of two random samples, each independently obtained from a different given population. The purpose of the test is to determine whether the difference between these two populations is statistically significant .

  4. Category:Statistical hypothesis testing - Wikipedia

    en.wikipedia.org/wiki/Category:Statistical...

    Print/export Download as PDF ... Pages in category "Statistical hypothesis testing" ... Two-proportion Z-test; Two-sample hypothesis testing; Type I and type II errors;

  5. 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. The vast majority of studies can be addressed by 30 of the 100 or so statistical tests in use. [3] [4] [5]

  6. Error exponents in hypothesis testing - Wikipedia

    en.wikipedia.org/wiki/Error_exponents_in...

    Download as PDF; Printable version ... In statistical hypothesis testing ... exponentially with the size of the sample used in the test. For example, ...

  7. Type III error - Wikipedia

    en.wikipedia.org/wiki/Type_III_error

    In statistical hypothesis testing, there are various notions of so-called type III errors (or errors of the third kind), and sometimes type IV errors or higher, by analogy with the type I and type II errors of Jerzy Neyman and Egon Pearson. Fundamentally, type III errors occur when researchers provide the right answer to the wrong question, i.e ...