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F. -test. An f-test pdf with d1 and d2 = 10, at a significance level of 0.05. (Red shaded region indicates the critical region) An F-test is any statistical test used to compare the variances of two samples or the ratio of variances between multiple samples. The test statistic, random variable F, is used to determine if the tested data has an F ...
Tukey's range test. 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. It can be used to correctly interpret the statistical significance of the difference between means ...
Critical values. Duncan's multiple range test makes use of the studentized range distribution in order to determine critical values for comparisons between means. Note that different comparisons between means may differ by their significance levels- since the significance level is subject to the size of the subset of means in question.
Critical point (mathematics) The (x-coordinates) of the red circles are ; the blue squares are . In mathematics, a critical point is the argument of a function where the function derivative is zero (or undefined, as specified below). The value of the function at a critical point is a critical value. [1]
In fluid mechanics, the Rayleigh number ( Ra, after Lord Rayleigh [1]) for a fluid is a dimensionless number associated with buoyancy -driven flow, also known as free (or natural) convection. [2] [3] [4] It characterises the fluid's flow regime: [5] a value in a certain lower range denotes laminar flow; a value in a higher range, turbulent flow.
Thermodynamics. In thermodynamics, the compressibility factor ( Z ), also known as the compression factor or the gas deviation factor, describes the deviation of a real gas from ideal gas behaviour. It is simply defined as the ratio of the molar volume of a gas to the molar volume of an ideal gas at the same temperature and pressure.
Grubbs's test. In statistics, Grubbs's test or the Grubbs test (named after Frank E. Grubbs, who published the test in 1950 [1] ), also known as the maximum normalized residual test or extreme studentized deviate test, is a test used to detect outliers in a univariate data set assumed to come from a normally distributed population.
In statistics, Dixon's Q test, or simply the Q test, is used for identification and rejection of outliers. This assumes normal distribution and per Robert Dean and Wilfrid Dixon, and others, this test should be used sparingly and never more than once in a data set. To apply a Q test for bad data, arrange the data in order of increasing values ...
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