**41.8****
****Fisher's Exact Test** (.NET, C#, CSharp, VB, Visual Basic, F#)

**StatsFunctions**
provides the FisherEactTest() method for
performing a Fisher's Exact Test for a specified
2 x 2 contingency table. Fisher's Exact
Test is a useful alternative to the chi-square test in cases where sample
sizes are small.

Fisher's Exact Test is so-called because the significance of the deviation from a null hypothesis can be calculated exactly, rather than relying on an approximation. The usual rule of thumb for deciding whether the chi-squared approximation is good enough is whether the expected values in all cells of the contingency table is greater than or equal to 5.

You can perform a Fisher's Exact Test by providing
the cell values directly, plus an **HypothesisType**
specifying the form of the alternative hypothesis:

Code Example – C# Fisher's exact test

int a = 12, b = 17, c = 4, d = 25;

double pvalue = StatsFunctions.FishersExactTest( a, b, c, d,

HypothesisType.TwoSided );

Code Example – VB Fisher's exact test

Dim A As Integer = 12

Dim B As Integer = 17

Dim C As Integer = 4

Dim D As Integer = 25

Dim PValue As Double = StatsFunctions.FishersExactTest(A, B, C, D, HypothesisType.TwoSided)

Values a, b, c and d are cell counts for contingency table:

a b

c d

If no hypothesis type is specified, FisherExactTest()
returns the lesser of the right and left tail *p*-value.

Overloads are also provided for data in an int[,] array or **DataFrame**
containg two **DFIntColumn**.