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  2. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    Example: To find 0.69, one would look down the rows to find 0.6 and then across the columns to 0.09 which would yield a probability of 0.25490 for a cumulative from mean table or 0.75490 from a cumulative table. To find a negative value such as –0.83, one could use a cumulative table for negative z-values [3] which yield a probability of 0.20327.

  3. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    To calculate the standardized statistic = (¯), we need to either know or have an approximate value for σ 2, from which we can calculate =. In some applications, σ 2 is known, but this is uncommon. If the sample size is moderate or large, we can substitute the sample variance for σ 2 , giving a plug-in test.

  4. One- and two-tailed tests - Wikipedia

    en.wikipedia.org/wiki/One-_and_two-tailed_tests

    The statistical tables for t and for Z provide critical values for both one- and two-tailed tests. That is, they provide the critical values that cut off an entire region at one or the other end of the sampling distribution as well as the critical values that cut off the regions (of half the size) at both ends of the sampling distribution.

  5. 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.

  6. Studentized range distribution - Wikipedia

    en.wikipedia.org/wiki/Studentized_range_distribution

    When only the equality of the two groups means is in question (i.e. whether μ 1 = μ 2), the studentized range distribution is similar to the Student's t distribution, differing only in that the first takes into account the number of means under consideration, and the critical value is adjusted accordingly. The more means under consideration ...

  7. Fisher's method - Wikipedia

    en.wikipedia.org/wiki/Fisher's_method

    Under Fisher's method, two small p-values P 1 and P 2 combine to form a smaller p-value.The darkest boundary defines the region where the meta-analysis p-value is below 0.05.. For example, if both p-values are around 0.10, or if one is around 0.04 and one is around 0.25, the meta-analysis p-value is around 0

  8. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Suppose the data can be realized from an N(0,1) distribution. For example, with a chosen significance level α = 0.05, from the Z-table, a one-tailed critical value of approximately 1.645 can be obtained. The one-tailed critical value C α ≈ 1.645 corresponds to the chosen significance level.

  9. Tukey's range test - Wikipedia

    en.wikipedia.org/wiki/Tukey's_range_test

    The value q s is the sample's test statistic. (The notation | x | means the absolute value of x; the magnitude of x with the sign set to +, regardless of the original sign of x.) This q s test statistic can then be compared to a q value for the chosen significance level α from a table of the studentized range distribution.