BUILTIN MATHEMATICA SYMBOL
BrownForsytheTest
 BrownForsytheTest performs a hypothesis test on data with null hypothesis that the true population variance , and alternative hypothesis that .
 Given and , BrownForsytheTest tests against .
 By default a probability value or value is returned.
 A small value suggests that it is unlikely that is true.
 The data in dspec must be univariate .
 The argument can be any positive real number.
 The BrownForsytheTest assumes that the data is normally distributed.
 The BrownForsytheTest is less sensitive to the assumption of normality than the LeveneTest.
 BrownForsytheTest[data, , "HypothesisTestData"] returns a HypothesisTestData object htd that can be used to extract additional test results and properties using the form htd["property"].
 BrownForsytheTest[data, , "property"] can be used to directly give the value of .
 Properties related to the reporting of test results include:

 "DegreesOfFreedom"  the degrees of freedom used in a test 
 "PValue"  list of values 
 "PValueTable"  formatted table of values 
 "ShortTestConclusion"  a short description of the conclusion of a test 
 "TestConclusion"  a description of the conclusion of a test 
 "TestData"  list of pairs of test statistics and values 
 "TestDataTable"  formatted table of values and test statistics 
 "TestStatistic"  list of test statistics 
 "TestStatisticTable"  formatted table of test statistics 
 When one sample of size is given, the BrownForsytheTest is equivalent to the FisherRatioTest.
 For two samples, the BrownForsytheTest is a modification of the LeveneTest that replaces the mean in Abs[data_{ij}Mean[data_{i}]] with a function . The function fn is generally chosen to be Median[data_{i}] but the TrimmedMean[data_{i}, 1/10] is used if the data is heavytailed.
 The following options can be used:

 For the BrownForsytheTest, a cutoff is chosen such that is rejected only if . The value of used for the and properties is controlled by the SignificanceLevel option. This value is also used in diagnostic tests of assumptions, including tests for normality and symmetry. By default is set to .
 Named settings for VerifyTestAssumptions in BrownForsytheTest include:

 "Normality"  verify that all data is normally distributed 
Test variances from two populations for equality:
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Create a HypothesisTestData object for further property extraction:
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Properties of the test:
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Test the ratio of the variances of two populations against a particular value:
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Perform the test with alternative hypothesis :
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