gov.sandia.cognition.statistics.method

Class FisherSignConfidence

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.method.FisherSignConfidence

All Implemented Interfaces:

NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

@ConfidenceTestAssumptions(name="Fisher Sign Test",
                           alsoKnownAs="Sign Test",
                           description={"Determines if there is a statistically significant between the means of two groups","A robust nonparameteric alternative to the paired Student\'s t-test."},
                           assumptions="The data from each group is sampled independently of each other.",
                           nullHypothesis="The means of the two groups is the same.",
                           dataPaired=true,
                           dataSameSize=true,
                           distribution=BinomialDistribution.CDF.class,
                           reference=@PublicationReference(author="Eric W. Weisstein",title="Fisher Sign Test",type=WebPage,year=2009,url="http://mathworld.wolfram.com/FisherSignTest.html"))
public class FisherSignConfidence
extends AbstractCloneableSerializable
implements NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>>

This is an implementation of the Fisher Sign Test, which is a robust nonparameteric test to determine if two groups have a different mean. However, because the test has essentially no assumptions, it generates very loose confidence bounds.

Since:

2.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	FisherSignConfidence.Statistic Contains the parameters from the Sign Test null-hypothesis evaluation

Constructor Summary

Constructors

Constructor and Description
FisherSignConfidence() Default Constructor

Method Summary

Modifier and Type	Method and Description
FisherSignConfidence.Statistic	evaluateNullHypothesis(java.util.Collection<? extends java.lang.Number> data1, java.util.Collection<? extends java.lang.Number> data2) Computes the probability that two data were generated by the same distribution.

Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable

clone

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Constructor Detail

FisherSignConfidence

public FisherSignConfidence()

Default Constructor

Method Detail

evaluateNullHypothesis

public FisherSignConfidence.Statistic evaluateNullHypothesis(java.util.Collection<? extends java.lang.Number> data1,
                                                             java.util.Collection<? extends java.lang.Number> data2)

Description copied from interface: NullHypothesisEvaluator

Computes the probability that two data were generated by the same distribution. NullHypothesisProbability=1 means that the distributions are likely the same, NullHypothesisProbability=0 means they are likely NOT the same, and NullHypothesisProbability less than 0.05 is the standard statistical significance test. This is the "p-value" that social scientists like to use.

Specified by:

evaluateNullHypothesis in interface NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>>

Parameters:

data1 - First dataset to consider

data2 - Second dataset to consider

Returns:

Probability that the two data were generated by the same source. A value of NullHypothesisProbability less than 0.05 is the standard point at which social scientists say two distributions were generated by different sources.