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Tukey's range test, also known as Tukey's test, Tukey method, Tukey's honest significance test, or Tukey's HSD (honestly significant difference) test, [1] is a single ...
Tukey’s Test (see also: Studentized Range Distribution) However, with the exception of Scheffès Method, these tests should be specified "a priori" despite being called "post-hoc" in conventional usage. For example, a difference between means could be significant with the Holm-Bonferroni method but not with the Turkey Test and vice versa.
Siegel–Tukey test, named after Sidney Siegel and John Tukey, is a non-parametric test which may be applied to data measured at least on an ordinal scale. It tests for differences in scale between two groups. The test is used to determine if one of two groups of data tends to have more widely dispersed values than the other.
Meant to squeeze all possible testing into the time before Eisenhower's test ban started on 30 October 1958. Planned as "Operation Millrace", changed to HT II when a science panel recommended to "stop testing after the Hardtack series." Nougat: 1961–1962 44: 44: 1: 2: small to 67 357: First all-underground test series.
This procedure is often used as a post-hoc test whenever a significant difference between three or more sample means has been revealed by an analysis of variance (ANOVA). [1] The Newman–Keuls method is similar to Tukey's range test as both procedures use studentized range statistics .
Henry Scheffé's simultaneous test of all contrasts in multiple comparison problems is the most [citation needed] well-known remedy in the case of analysis of variance. [1] It is a method designed for testing hypotheses suggested by the data while avoiding the fallacy described above.
Rodger’s approach was formulated within the Neyman-Pearson hypothesis-testing framework [...] and required that the test of each contrast Ψ i (i = 1, ... , J − 1) should result in a ‘decision’ between the null hypothesis (i H 0: Ψ i = 0) and a particular value δ i specified a priori by the alternative hypothesis (i H 1: Ψ i = δ i ...
Actually, testing means' differences is done by the quadratic rational F statistic ( F=MSB/MSW). In order to determine which mean differs from another mean or which contrast of means are significantly different, Post Hoc tests (Multiple Comparison tests) or planned tests should be conducted after obtaining a significant omnibus F test.