Accord.Statistics.Testing Namespace 
Class  Description  

AndersonDarlingTest 
Onesample AndersonDarling (AD) test.
 
AnovaSourceCollection 
ANOVA's result table.
 
AnovaVariationSource 
Source of variation in an ANOVA experiment.
 
AverageKappaTest 
Kappa Test for multiple contingency tables.
 
BartlettTest 
Bartlett's test for equality of variances.
 
BhapkarTest 
Bhapkar test of homogeneity for contingency tables.
 
BinomialTest 
Binomial test.
 
BowkerTest 
Bowker test of symmetry for contingency tables.
 
ChiSquareTest 
TwoSample (Goodnessoffit) ChiSquare Test (Upper Tail)
 
FisherExactTest 
Fisher's exact test for contingency tables.
 
FTest 
Snedecor's FTest.
 
GrubbTest 
Grubb's Test for Outliers (for approximately Normal distributions).
 
HypothesisTestTDistribution 
Base class for Hypothesis Tests.
 
KappaTest 
Kappa Test for agreement in contingency tables.
 
KolmogorovSmirnovTest 
Onesample KolmogorovSmirnov (KS) test.
 
LeveneTest 
Levene's test for equality of variances.
 
LillieforsTest 
One sample Lilliefors' corrected KolmogorovSmirnov (KS) test.
 
MannWhitneyWilcoxonTest 
MannWhitneyWilcoxon test for unpaired samples.
 
McNemarTest 
McNemar test of homogeneity for 2 x 2 contingency tables.
 
MultinomialTest 
Multinomial test (approximated).
 
OneWayAnova 
Oneway Analysis of Variance (ANOVA).
 
PairedTTest 
TTest for two paired samples.
 
ReceiverOperatingCurveTest 
Hypothesis test for a single ROC curve.
 
ShapiroWilkTest 
ShapiroWilk test for normality.
 
SignTest 
Sign test for the median.
 
StuartMaxwellTest 
StuartMaxwell test of homogeneity for K x K contingency tables.
 
TTest 
Onesample Student's T test.
 
TwoAverageKappaTest 
Kappa test for the average of two groups of contingency tables.
 
TwoMatrixKappaTest 
Kappa Test for two contingency tables.
 
TwoProportionZTest 
ZTest for two sample proportions.
 
TwoReceiverOperatingCurveTest 
Hypothesis test for two ReceiverOperating
Characteristic (ROC) curve areas (ROCAUC).
 
TwoSampleKolmogorovSmirnovTest 
Twosample KolmogorovSmirnov (KS) test.
 
TwoSampleSignTest 
Sign test for two paired samples.
 
TwoSampleTTest 
Twosample Student's T test.
 
TwoSampleWilcoxonSignedRankTest 
Wilcoxon signedrank test for paired samples.
 
TwoSampleZTest 
Two sample ZTest.
 
TwoWayAnova 
Twoway Analysis of Variance.
 
TwoWayAnovaVariationSources 
Sources of variation in a twoway ANOVA experiment.
 
WaldTest 
Wald's Test using the Normal distribution.
 
WilcoxonSignedRankTest 
Wilcoxon signedrank test for the median.
 
WilcoxonTest 
Base class for Wilcoxon's W tests.
 
ZTest 
Onesample ZTest (location test).

Interface  Description  

IAnova 
Common interface for analyses of variance.
 
IHypothesisTest 
Common interface for Hypothesis tests depending on a statistical distribution.
 
IHypothesisTestTDistribution 
Common interface for Hypothesis tests depending on a statistical distribution.

Enumeration  Description  

DistributionTail 
Hypothesis type
 
GrubbTestHypothesis 
Hypothesis for the onesample Grubb's test.
 
KolmogorovSmirnovTestHypothesis 
Hypothesis for the onesample KolmogorovSmirnov test.
 
LeveneTestMethod 
Levene test computation methods.
 
OneSampleHypothesis  
TwoSampleHypothesis 
Common test Hypothesis for two sample tests, such as
TwoSampleZTest and TwoSampleTTest.
 
TwoSampleKolmogorovSmirnovTestHypothesis 
Test hypothesis for the twosample KolmogorovSmirnov tests.
 
TwoWayAnovaModel 
Twoway ANOVA model types.

This namespace contains a suite of parametric and nonparametric 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. PValues are also ready to be inspected by checking a test's PValue 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 nonparametric 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 interrater 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.