Uses of Interface
org.apache.commons.statistics.inference.SignificanceResult
Packages that use SignificanceResult
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Uses of SignificanceResult in org.apache.commons.statistics.inference
Classes in org.apache.commons.statistics.inference that implement SignificanceResultModifier and TypeClassDescription(package private) class
Base implementation for the result of a test for significance.static class
Result for the one-sample Kolmogorov-Smirnov test.static final class
Result for the two-sample Kolmogorov-Smirnov test.static final class
Result for the Mann-Whitney U test.static final class
Result for the one-way ANOVA.static final class
Result for the t-test.static final class
Result for the unconditioned exact test.static final class
Result for the Wilcoxon signed-rank test.Methods in org.apache.commons.statistics.inference that return SignificanceResultModifier and TypeMethodDescriptionBinomialTest.test
(int numberOfTrials, int numberOfSuccesses, double probability) Performs a binomial test about the probability of success \( \pi \).ChiSquareTest.test
(double[] expected, long[] observed) Perform a chi-square goodness-of-fit test evaluating the null hypothesis that theobserved
counts conform to theexpected
counts.ChiSquareTest.test
(long[] observed) Perform a chi-square goodness-of-fit test evaluating the null hypothesis that theobserved
counts conform to a uniform distribution (each category is equally likely).ChiSquareTest.test
(long[][] counts) Perform a chi-square test of independence based on the inputcounts
array, viewed as a two-way table.ChiSquareTest.test
(long[] observed1, long[] observed2) Perform a chi-square test of independence of frequency counts inobserved1
andobserved2
.FisherExactTest.test
(int[][] table) Performs Fisher's exact test on the 2-by-2 contingency table.GTest.test
(double[] expected, long[] observed) Perform a G-test for goodness-of-fit evaluating the null hypothesis that theobserved
counts conform to theexpected
counts.GTest.test
(long[] observed) Perform a G-test for goodness-of-fit evaluating the null hypothesis that theobserved
counts conform to a uniform distribution (each category is equally likely).GTest.test
(long[][] counts) Perform a G-test of independence based on the inputcounts
array, viewed as a two-way table.