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However, the studentized range distribution used to determine the level of significance of the differences considered in Tukey's test has vastly broader application: It is useful for researchers who have searched their collected data for remarkable differences between groups, but then cannot validly determine how significant their discovered ...
Outside of such a specialized audience, the test output as shown below is rather challenging to interpret. Tukey's Range Test results for five West Coast cities rainfall data. The Tukey's range test uncovered that San Francisco & Spokane did not have statistically different rainfall mean (at the alpha = 0.05 level) with a p-value of 0.08.
Tukey's test is either: Tukey's range test, also called Tukey method, Tukey's honest significance test, Tukey's HSD ... Statistics; Cookie statement;
In statistics, Tukey's test of additivity, [1] named for John Tukey, is an approach used in two-way ANOVA (regression analysis involving two qualitative factors) to assess whether the factor variables (categorical variables) are additively related to the expected value of the response variable. It can be applied when there are no replicated ...
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. The vast majority of studies can be addressed by 30 of the 100 or so statistical tests in use. [3] [4] [5]
It is identical to a Tukey mean-difference plot, [1] the name by which it is known in other fields, but was popularised in medical statistics by J. Martin Bland and Douglas G. Altman. [ 2 ] [ 3 ] Construction
The chemotherapy drug 5-FU can be toxic to some people with cancer. A quick, cheap test can show if chemo is safe for a patient, but few doctors order it.
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]