public class Bartlett extends HypothesisTest
k samples are from populations with equal variances, hence homoscedasticity.
Some statistical tests, for example the analysis of variance, assume that variances are equal across groups or samples.
The Bartlett test can be used to verify that assumption.
Bartlett's test is sensitive to departures from normality.
That is, if the samples come from non-normal distributions, then Bartlett's test may simply be testing for non-normality.
The Levene and BrownForsythe tests are alternatives to the Bartlett test that are less sensitive to departures from normality.
The R equivalent function is bartlett.test.
| Modifier and Type | Field and Description |
|---|---|
double |
df
the degree of freedom
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k, N, pValue, testStatistics| Constructor and Description |
|---|
Bartlett(double[]... samples)
Perform the Bartlett test to test if the samples are from populations with equal variances.
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| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
getAlternativeHypothesis()
Get a description of the alternative hypothesis.
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java.lang.String |
getNullHypothesis()
Get a description of the null hypothesis.
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isNullRejected, oneSidedPvalue, pValue, statisticspublic Bartlett(double[]... samples)
samples - samplespublic java.lang.String getNullHypothesis()
HypothesisTestgetNullHypothesis in class HypothesisTestpublic java.lang.String getAlternativeHypothesis()
HypothesisTestgetAlternativeHypothesis in class HypothesisTest