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  2. 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.

  3. 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.

  4. Test statistic - Wikipedia

    en.wikipedia.org/wiki/Test_statistic

    However, a test statistic is specifically intended for use in statistical testing, whereas the main quality of a descriptive statistic is that it is easily interpretable. Some informative descriptive statistics, such as the sample range, do not make good test statistics since it is difficult to determine their sampling distribution. Two widely ...

  5. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4] The parameters used are:

  6. Power (statistics) - Wikipedia

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

    The following is an example that shows how to compute power for a randomized experiment: Suppose the goal of an experiment is to study the effect of a treatment on some quantity, and so we shall compare research subjects by measuring the quantity before and after the treatment, analyzing the data using a one-sided paired t-test, with a ...

  7. Student's t-test - Wikipedia

    en.wikipedia.org/wiki/Student's_t-test

    Most test statistics have the form t = Z/s, where Z and s are functions of the data. Z may be sensitive to the alternative hypothesis (i.e., its magnitude tends to be larger when the alternative hypothesis is true), whereas s is a scaling parameter that allows the distribution of t to be determined. As an example, in the one-sample t-test

  8. Validity (statistics) - Wikipedia

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

    The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.

  9. Reliability (statistics) - Wikipedia

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

    For example, alternate forms exist for several tests of general intelligence, and these tests are generally seen equivalent. [7] With the parallel test model it is possible to develop two forms of a test that are equivalent in the sense that a person's true score on form A would be identical to their true score on form B.