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  2. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    In statistics, a standard normal table, also called the unit normal table or Z table, [1] is a mathematical table for the values of Φ, the cumulative distribution function of the normal distribution.

  3. 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.

  4. Z table - Wikipedia

    en.wikipedia.org/?title=Z_table&redirect=no

    This page was last edited on 21 February 2007, at 16:55 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable.The general form of its probability density function is [2] [3] = ().

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  7. Studentized range distribution - Wikipedia

    en.wikipedia.org/wiki/Studentized_range_distribution

    Critical values of the studentized range distribution are used in Tukey's range test. [3]The studentized range is used to calculate significance levels for results obtained by data mining, where one selectively seeks extreme differences in sample data, rather than only sampling randomly.

  8. Zeta distribution - Wikipedia

    en.wikipedia.org/wiki/Zeta_distribution

    In probability theory and statistics, the zeta distribution is a discrete probability distribution.If X is a zeta-distributed random variable with parameter s, then the probability that X takes the positive integer value k is given by the probability mass function

  9. Confidence distribution - Wikipedia

    en.wikipedia.org/wiki/Confidence_Distribution

    Classically, a confidence distribution is defined by inverting the upper limits of a series of lower-sided confidence intervals. [15] [16] [page needed] In particular, For every α in (0, 1), let (−∞, ξ n (α)] be a 100α% lower-side confidence interval for θ, where ξ n (α) = ξ n (X n,α) is continuous and increasing in α for each sample X n.