FTest Class 
Namespace: Accord.Statistics.Testing
The FTest type exposes the following members.
Name  Description  

FTest 
Creates a new FTest.
 
FTest(Double, Int32, Int32, TwoSampleHypothesis) 
Creates a new FTest for a given statistic with given degrees of freedom.
 
FTest(Double, Double, Int32, Int32, TwoSampleHypothesis) 
Creates a new FTest for a given statistic with given degrees of freedom.

Name  Description  

CriticalValue 
Gets the critical value for the current significance level.
(Inherited from HypothesisTestTDistribution.)  
DegreesOfFreedom1 
Gets the degrees of freedom for the
numerator in the test distribution.
 
DegreesOfFreedom2 
Gets the degrees of freedom for the
denominator in the test distribution.
 
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 Ftest.
 
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.)  
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.)  
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 Matrix.) 
A Ftest is any statistical test in which the test statistic has an Fdistribution under the null hypothesis. It is most often used when comparing statistical models that have been fit to a data set, in order to identify the model that best fits the population from which the data were sampled.
References:
// The following example has been based on the page "FTest for Equality // of Two Variances", from NIST/SEMATECH eHandbook of Statistical Methods: // // http://www.itl.nist.gov/div898/handbook/eda/section3/eda359.htm // // Consider a data set containing 480 ceramic strength // measurements for two batches of material. The summary // statistics for each batch are shown below: // Batch 1: int numberOfObservations1 = 240; // double mean1 = 688.9987; double stdDev1 = 65.54909; double var1 = stdDev1 * stdDev1; // Batch 2: int numberOfObservations2 = 240; // double mean2 = 611.1559; double stdDev2 = 61.85425; double var2 = stdDev2 * stdDev2; // Here, we will be testing the null hypothesis that // the variances for the two batches are equal. int degreesOfFreedom1 = numberOfObservations1  1; int degreesOfFreedom2 = numberOfObservations2  1; // Now we can create a FTest to test the difference between variances var ftest = new FTest(var1, var2, degreesOfFreedom1, degreesOfFreedom2); double statistic = ftest.Statistic; // 1.123037 double pvalue = ftest.PValue; // 0.185191 bool significant = ftest.Significant; // false // The F test indicates that there is not enough evidence // to reject the null hypothesis that the two batch variances // are equal at the 0.05 significance level.