FisherExactTest Class 
Namespace: Accord.Statistics.Testing
[SerializableAttribute] public class FisherExactTest : HypothesisTest<HypergeometricDistribution>
The FisherExactTest type exposes the following members.
Name  Description  

FisherExactTest 
Constructs a new Fisher's exact test.

Name  Description  

CriticalValue 
Gets the critical value for the current significance level.
(Inherited from HypothesisTestTDistribution.)  
Hypothesis 
Gets the alternative hypothesis under test. If the test is
Significant, the null hypothesis
can be rejected in favor of this alternative hypothesis.
 
PValue 
Gets the Pvalue associated with this test.
(Inherited from HypothesisTestTDistribution.)  
Significant 
Gets whether the null hypothesis should be rejected.
(Inherited from HypothesisTestTDistribution.)  
Size 
Gets the significance level for the
test. Default value is 0.05 (5%).
(Inherited from HypothesisTestTDistribution.)  
Statistic 
Gets the test statistic.
(Inherited from HypothesisTestTDistribution.)  
StatisticDistribution 
Gets the distribution associated
with the test statistic.
(Inherited from HypothesisTestTDistribution.)  
Tail 
Gets the test type.
(Inherited from HypothesisTestTDistribution.) 
Name  Description  

Compute 
Computes the Fisher's exact test.
 
Equals  Determines whether the specified object is equal to the current object. (Inherited from Object.)  
Finalize  Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)  
GetHashCode  Serves as the default hash function. (Inherited from Object.)  
GetType  Gets the Type of the current instance. (Inherited from Object.)  
MemberwiseClone  Creates a shallow copy of the current Object. (Inherited from Object.)  
OnSizeChanged 
Called whenever the test significance level changes.
(Inherited from HypothesisTestTDistribution.)  
PValueToStatistic 
Converts a given pvalue to a test statistic.
(Overrides HypothesisTestTDistributionPValueToStatistic(Double).)  
StatisticToPValue 
Converts a given test statistic to a pvalue.
(Overrides HypothesisTestTDistributionStatisticToPValue(Double).)  
ToString 
Converts the numeric PValue of this test to its equivalent string representation.
(Inherited from HypothesisTestTDistribution.)  
ToString(String, IFormatProvider) 
Converts the numeric PValue of this test to its equivalent string representation.
(Inherited from HypothesisTestTDistribution.) 
Name  Description  

HasMethod 
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)  
IsEqual 
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.)  
To(Type)  Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)  
ToT  Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) 
This test statistic distribution is the Hypergeometric.
// Example from https://en.wikipedia.org/wiki/Fisher%27s_exact_test // This example comes directly from the Wikipedia page referenced above. In this example, // a sample of teenagers might be divided into male and female on the one hand, and those // that are and are not currently studying for a statistics exam on the other. We hypothesize, // for example, that the proportion of studying individuals is higher among the women than // among the men, and we want to test whether any difference of proportions that we observe // is significant. The data might look like this: var matrix = new ConfusionMatrix(new int[,] { /* Men Women */ /* Studying */ { 1, 9 }, /* Notstudying*/ { 11, 3 }, }); // Let's check that the row totals and column // totals match the ones reported in Wikipedia: int[] rowTotals = matrix.RowTotals; // should be 10, 14 int[] colTotals = matrix.ColumnTotals; // should be 12, 12 int total = matrix.NumberOfSamples; // should be 24 // The question we ask about these data is: knowing that 10 of these 24 teenagers are studiers, // and that 12 of the 24 are female, and assuming the null hypothesis that men and women are // equally likely to study, what is the probability that these 10 studiers would be so unevenly // distributed between the women and the men? If we were to choose 10 of the teenagers at random, // what is the probability that 9 or more of them would be among the 12 women, and only 1 or fewer // from among the 12 men? var fet = new FisherExactTest(matrix, alternate: OneSampleHypothesis.ValueIsDifferentFromHypothesis); double p = fet.PValue; // should be approximately 0.0027594561852200832 bool significant = fet.Significant; // should be true // The same result can be verified in R using: // fisher.test(matrix(c(1, 9, 11, 3), 2,2)) /* Fisher's Exact Test for Count Data data: matrix(c(1, 9, 11, 3), 2, 2) p  value = 0.002759 alternative hypothesis: true odds ratio is not equal to 1 95 percent confidence interval: 0.0006438284 0.4258840381 sample estimates: odds ratio 0.03723312*/