gov.sandia.cognition.statistics.method

Class MannWhitneyUConfidence

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.method.MannWhitneyUConfidence

All Implemented Interfaces:

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

@ConfidenceTestAssumptions(name="Mann-Whitney U-test",
                           alsoKnownAs={"Mann-Whitney-Wolcoxon","Wilcoxon rank-sum test","Wilcoxon-Mann-Whitney test","U-test"},
                           description="A nonparameteric test to determine is two groups of data were drawn from the same underlying distribution.",
                           assumptions={"The groups were sampled independently.","The data are orginal and we can determine which of two samples is greater than the other.","Although the two populations don\'t have to follow any particular distribution, the two distributions must have a similar shape."},
                           nullHypothesis="The data were drawn from the same distribution.",
                           dataPaired=false,
                           dataSameSize=false,
                           distribution=UnivariateGaussian.CDF.class,
                           reference=@PublicationReference(author="Wikipedia",title="Mann-Whitney U",type=WebPage,year=2009,url="http://en.wikipedia.org/wiki/Mann-Whitney_U"))
public class MannWhitneyUConfidence
extends AbstractCloneableSerializable
implements NullHypothesisEvaluator<java.util.Collection<? extends java.lang.Number>>

Performs a Mann-Whitney U-test on the given data (usually simply called a "U-test", sometimes called a Wilcoxon-Mann-Whitney U-test, or Wilcoxon rank-sum test).

Since:

2.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	MannWhitneyUConfidence.Statistic Statistics from the Mann-Whitney U-test

Constructor Summary

Constructors

Constructor and Description
MannWhitneyUConfidence() Creates a new instance of MannWhitneyUConfidence

Method Summary

Modifier and Type	Method and Description
MannWhitneyUConfidence.Statistic	evaluateNullHypothesis(java.util.Collection<? extends InputOutputPair<? extends java.lang.Number,java.lang.Boolean>> scoreClassPairs) Performs a U-test on the score-class pairs.
MannWhitneyUConfidence.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

MannWhitneyUConfidence

public MannWhitneyUConfidence()

Creates a new instance of MannWhitneyUConfidence

Method Detail

evaluateNullHypothesis

public MannWhitneyUConfidence.Statistic evaluateNullHypothesis(java.util.Collection<? extends InputOutputPair<? extends java.lang.Number,java.lang.Boolean>> scoreClassPairs)

Performs a U-test on the score-class pairs. The first element in the pair is a score, the second is a flag to determine which group the score belongs to. For example {, means that data1=1.0 and data2=0.9 and so forth. This is useful for computing that classified data partitions data better than chance.

Parameters:

scoreClassPairs - Pairs of scores with the corresponding class "label" for the score

Returns:

Statistics from the Mann-Whitney U-test

evaluateNullHypothesis

public MannWhitneyUConfidence.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.