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Accord.Statistics.Testing Namespace |
Classes| Class | Description | |
|---|---|---|
  | AndersonDarlingTest |
One-sample Anderson-Darling (AD) test.
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| AnovaSourceCollection |
ANOVA's result table.
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| AnovaVariationSource |
Source of variation in an ANOVA experiment.
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| AverageKappaTest |
Kappa Test for multiple contingency tables.
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| BartlettTest |
Bartlett's test for equality of variances.
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| BhapkarTest |
Bhapkar test of homogeneity for contingency tables.
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| BinomialTest |
Binomial test.
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| BowkerTest |
Bowker test of symmetry for contingency tables.
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| ChiSquareTest |
Two-Sample (Goodness-of-fit) Chi-Square Test (Upper Tail)
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| FisherExactTest |
Fisher's exact test for contingency tables.
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| FTest |
Snedecor's F-Test.
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| GrubbTest |
Grubb's Test for Outliers (for approximately Normal distributions).
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| HypothesisTestTDistribution |
Base class for Hypothesis Tests.
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| KappaTest |
Kappa Test for agreement in contingency tables.
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| KolmogorovSmirnovTest |
One-sample Kolmogorov-Smirnov (KS) test.
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| LeveneTest |
Levene's test for equality of variances.
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| LillieforsTest |
One sample Lilliefors' corrected Kolmogorov-Smirnov (KS) test.
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| MannWhitneyWilcoxonTest |
Mann-Whitney-Wilcoxon test for unpaired samples.
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| McNemarTest |
McNemar test of homogeneity for 2 x 2 contingency tables.
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| MultinomialTest |
Multinomial test (approximated).
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| OneWayAnova |
One-way Analysis of Variance (ANOVA).
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| PairedTTest |
T-Test for two paired samples.
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| ReceiverOperatingCurveTest |
Hypothesis test for a single ROC curve.
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| ShapiroWilkTest |
Shapiro-Wilk test for normality.
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| SignTest |
Sign test for the median.
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| StuartMaxwellTest |
Stuart-Maxwell test of homogeneity for K x K contingency tables.
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| TTest |
One-sample Student's T test.
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| TwoAverageKappaTest |
Kappa test for the average of two groups of contingency tables.
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| TwoMatrixKappaTest |
Kappa Test for two contingency tables.
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| TwoProportionZTest |
Z-Test for two sample proportions.
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| TwoReceiverOperatingCurveTest |
Hypothesis test for two Receiver-Operating
Characteristic (ROC) curve areas (ROC-AUC).
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| TwoSampleKolmogorovSmirnovTest |
Two-sample Kolmogorov-Smirnov (KS) test.
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| TwoSampleSignTest |
Sign test for two paired samples.
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| TwoSampleTTest |
Two-sample Student's T test.
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| TwoSampleWilcoxonSignedRankTest |
Wilcoxon signed-rank test for paired samples.
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| TwoSampleZTest |
Two sample Z-Test.
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| TwoWayAnova |
Two-way Analysis of Variance.
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| TwoWayAnovaVariationSources |
Sources of variation in a two-way ANOVA experiment.
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| WaldTest |
Wald's Test using the Normal distribution.
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| WilcoxonSignedRankTest |
Wilcoxon signed-rank test for the median.
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| WilcoxonTest |
Base class for Wilcoxon's W tests.
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| ZTest |
One-sample Z-Test (location test).
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Interfaces| Interface | Description | |
|---|---|---|
 | IAnova |
Common interface for analyses of variance.
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| IHypothesisTest |
Common interface for Hypothesis tests depending on a statistical distribution.
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| IHypothesisTestTDistribution |
Common interface for Hypothesis tests depending on a statistical distribution.
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Enumerations| Enumeration | Description | |
|---|---|---|
 | DistributionTail |
Hypothesis type
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| GrubbTestHypothesis |
Hypothesis for the one-sample Grubb's test.
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| KolmogorovSmirnovTestHypothesis |
Hypothesis for the one-sample Kolmogorov-Smirnov test.
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| LeveneTestMethod |
Levene test computation methods.
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| OneSampleHypothesis | |
| TwoSampleHypothesis |
Common test Hypothesis for two sample tests, such as
TwoSampleZTest and TwoSampleTTest.
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| TwoSampleKolmogorovSmirnovTestHypothesis |
Test hypothesis for the two-sample Kolmogorov-Smirnov tests.
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| TwoWayAnovaModel |
Two-way ANOVA model types.
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RemarksThis namespace contains a suite of parametric and non-parametric hypothesis tests. Every test in this library implements the IHypothesisTest interface, which defines a few key methods and properties to assert whether an statistical hypothesis can be supported or not. Every hypothesis test is associated with an statistic distribution which can in turn be queried, inspected and computed as any other distribution in the Accord.Statistics.Distributionsnamespace.
By default, tests are created using a 0.05 significance level , which in the framework is referred as the test's size. P-Values are also ready to be inspected by checking a test's P-Value property.
Furthermore, several tests in this namespace also support power analysis. The power analysis of a test can be used to suggest an optimal number of samples which have to be obtained in order to achieve a more interpretable or useful result while doing hypothesis testing. Power analyses implement the IPowerAnalysis interface, and analyses are available for the one sample Z, and T tests, as well as their two sample versions.
Some useful parametric tests are the BinomialTest, ChiSquareTest, FTest, MultinomialTest, TTest, WaldTest and ZTest. Useful non-parametric tests include the KolmogorovSmirnovTest, SignTest, WilcoxonSignedRankTest and the WilcoxonTest.
Tests are also available for two or more samples. In this case, we can find two sample variants for the PairedTTest, TwoProportionZTest, TwoSampleKolmogorovSmirnovTest, TwoSampleSignTest, TwoSampleTTest, TwoSampleWilcoxonSignedRankTest, TwoSampleZTest, as well as the MannWhitneyWilcoxonTest for unpaired samples. For multiple samples we can find the OneWayAnova and TwoWayAnova, as well as the LeveneTest and BartlettTest.
Finally, the namespace also includes several tests for contingency tables. Those tests include Kappa test for inter-rater agreement and its variants, such as the AverageKappaTest, TwoAverageKappaTest and TwoMatrixKappaTest. Other tests include BhapkarTest, McNemarTest, ReceiverOperatingCurveTest, StuartMaxwellTest, and the TwoReceiverOperatingCurveTest.
The namespace class diagram is shown below.
Please note that class diagrams for each of the inner namespaces are also available within their own documentation pages.
See Also