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  2. File:High School Probability and Statistics (Basic).pdf

    en.wikipedia.org/wiki/File:High_School...

    Original file (1,275 × 1,650 pixels, file size: 6.82 MB, MIME type: application/pdf, 156 pages) This is a file from the Wikimedia Commons . Information from its description page there is shown below.

  3. File:High School Probability and Statistics Teacher's Guide.pdf

    en.wikipedia.org/wiki/File:High_School...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  4. List of statistical tests - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_tests

    [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 .

  5. 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.

  6. Kolmogorov–Smirnov test - Wikipedia

    en.wikipedia.org/wiki/Kolmogorov–Smirnov_test

    Illustration of the Kolmogorov–Smirnov statistic. The red line is a model CDF, the blue line is an empirical CDF, and the black arrow is the KS statistic.. Kolmogorov–Smirnov test (K–S test or KS test) is a nonparametric test of the equality of continuous (or discontinuous, see Section 2.2), one-dimensional probability distributions that can be used to test whether a sample came from a ...

  7. Score test - Wikipedia

    en.wikipedia.org/wiki/Score_test

    If the null hypothesis is true, the likelihood ratio test, the Wald test, and the Score test are asymptotically equivalent tests of hypotheses. [8] [9] When testing nested models, the statistics for each test then converge to a Chi-squared distribution with degrees of freedom equal to the difference in degrees of freedom in the two models. If ...