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  2. t-statistic - Wikipedia

    en.wikipedia.org/wiki/T-statistic

    Most frequently, t statistics are used in Student's t-tests, a form of statistical hypothesis testing, and in the computation of certain confidence intervals. The key property of the t statistic is that it is a pivotal quantity – while defined in terms of the sample mean, its sampling distribution does not depend on the population parameters, and thus it can be used regardless of what these ...

  3. Student's t-test - Wikipedia

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

    However, in practice the distribution is rarely used, since tabulated values for T 2 are hard to find. Usually, T 2 is converted instead to an F statistic. For a one-sample multivariate test, the hypothesis is that the mean vector (μ) is equal to a given vector (μ 0). The test statistic is Hotelling's t 2:

  4. Student's t-distribution - Wikipedia

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

    For the statistic t, with ν degrees of freedom, A(t | ν) is the probability that t would be less than the observed value if the two means were the same (provided that the smaller mean is subtracted from the larger, so that t ≥ 0). It can be easily calculated from the cumulative distribution function F ν (t) of the t distribution:

  5. 97.5th percentile point - Wikipedia

    en.wikipedia.org/wiki/97.5th_percentile_point

    There is no single accepted name for this number; it is also commonly referred to as the "standard normal deviate", "normal score" or "Z score" for the 97.5 percentile point, the .975 point, or just its approximate value, 1.96. If X has a standard normal distribution, i.e. X ~ N(0,1),

  6. Standard score - Wikipedia

    en.wikipedia.org/wiki/Standard_score

    Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.

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  8. Jonckheere's trend test - Wikipedia

    en.wikipedia.org/wiki/Jonckheere's_Trend_Test

    Where n is the total number of scores, and t i is the number of scores in the ith sample. The approximation to the standard normal distribution can be improved by the use of a continuity correction: S c = |S| – 1. Thus 1 is subtracted from a positive S value and 1 is added to a negative S value. The z-score equivalent is then given by

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