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  2. Paper and ink testing - Wikipedia

    en.wikipedia.org/wiki/Paper_and_ink_testing

    Ink requirement is defined as the amount of ink needed to print a unit area with a standard Solid Ink Density. For newsprint, the ISO 12647-3 specification is C 0.90, M 0.90, Y 0.90 and K 1.10, Status E, D50, 2o, density minus paper with polarization filter. Ink requirement is measured as g/m2 (grams of ink required to print 1 m2 of paper)

  3. Yates's correction for continuity - Wikipedia

    en.wikipedia.org/wiki/Yates's_correction_for...

    This reduces the chi-squared value obtained and thus increases its p-value. The effect of Yates's correction is to prevent overestimation of statistical significance for small data. This formula is chiefly used when at least one cell of the table has an expected count smaller than 5.

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

  5. Bartlett's test - Wikipedia

    en.wikipedia.org/wiki/Bartlett's_test

    The test procedure due to M.S.E (Mean Square Error/Estimator) Bartlett test is represented here. 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 ...

  6. Hosmer–Lemeshow test - Wikipedia

    en.wikipedia.org/wiki/Hosmer–Lemeshow_test

    Print/export Download as PDF ... 1 0 30 10 0.33 2 50 30 13 0.43 ... The Pearson chi-squared goodness of fit test provides a method to test if the observed and ...

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  8. Cochran–Armitage test for trend - Wikipedia

    en.wikipedia.org/wiki/Cochran–Armitage_test_for...

    where R 1 = N 11 + N 12 + N 13, and C 1 = N 11 + N 21, etc. . The trend test statistic is = (), where the t i are weights, and the difference N 1i R 2 −N 2i R 1 can be seen as the difference between N 1i and N 2i after reweighting the rows to have the same total.

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