Hartley's test

In statistics, Hartley's test, also known as the Fmax test or Hartley's Fmax, is used in the analysis of variance to verify that different groups have a similar variance, an assumption needed for other statistical tests. ^[1]

10 relations: Analysis of variance, Bartlett's test, Brown–Forsythe test, Cochran's C test, Herman Otto Hartley, Normal distribution, Ratio, Sampling distribution, Statistics, Variance.

Analysis of variance

Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among group means in a sample.

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Bartlett's test

In statistics, Bartlett's test (see Snedecor and Cochran, 1989) is used to test if k samples are from populations with equal variances.

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Brown–Forsythe test

The Brown–Forsythe test is a statistical test for the equality of group variances based on performing an ANOVA on a transformation of the response variable.

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Cochran's C test

In statistics, Cochran's C test, named after William G. Cochran, is a one-sided upper limit variance outlier test.

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Herman Otto Hartley

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Normal distribution

In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.

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Ratio

In mathematics, a ratio is a relationship between two numbers indicating how many times the first number contains the second.

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Sampling distribution

In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic.

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Statistics

Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.

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Variance

In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its mean.

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References

[1] https://en.wikipedia.org/wiki/Hartley's_test

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