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In statistics, the Tukey–Duckworth test is a two-sample location test – a statistical test of whether one of two samples was significantly greater than the other. It was introduced by John Tukey, who aimed to answer a request by W. E. Duckworth for a test simple enough to be remembered and applied in the field without recourse to tables, let alone computers.
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-step multiple comparison procedure and statistical test.
In statistical hypothesis testing, a two-sample test is a test performed on the data of two random samples, each independently obtained from a different given population. The purpose of the test is to determine whether the difference between these two populations is statistically significant .
A location test is a statistical hypothesis test that compares the location parameter of a statistical population to a given constant, ...
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.
John Wilder Tukey (/ ˈ t uː k i /; June 16, 1915 – July 26, 2000) was an American mathematician and statistician, best known for the development of the fast Fourier Transform (FFT) algorithm and box plot. [2] The Tukey range test, the Tukey lambda distribution, the Tukey test of additivity, and the Teichmüller–Tukey lemma all bear his
Tukey's test is either: Tukey's range test, also called Tukey method, Tukey's honest significance test, Tukey's HSD (Honestly Significant Difference) test;
Location testing for Gaussian scale mixture distributions; M. ... Tukey–Duckworth test; Tukey's range test; Tukey's test of additivity; Two-proportion Z-test; V.