gov.sandia.cognition.statistics.method
Class FisherSignConfidence

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.statistics.method.FisherSignConfidence
All Implemented Interfaces:
NullHypothesisEvaluator<Collection<? extends Number>>, CloneableSerializable, Serializable, 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<Collection<? extends 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
static class FisherSignConfidence.Statistic
          Contains the parameters from the Sign Test null-hypothesis evaluation
 
Constructor Summary
FisherSignConfidence()
          Default Constructor
 
Method Summary
 FisherSignConfidence.Statistic evaluateNullHypothesis(Collection<? extends Number> data1, Collection<? extends 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(Collection<? extends Number> data1,
                                                             Collection<? extends 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<Collection<? extends 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.