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java.lang.Object gov.sandia.cognition.util.AbstractCloneableSerializable gov.sandia.cognition.statistics.method.GaussianConfidence
@ConfidenceTestAssumptions(name="Gaussian Ztest", alsoKnownAs="Ztest", description="Determines if two populations have the same mean, if the populations are Gaussian and relatively large, at least 30 or so.", assumptions={"The two groups are sampled independently of each other.","The two groups are sampled from a Gaussian distribution, or the underlying distributions are nonGaussian but obey the weak law of large numbers.","The variances of the two groups are equal."}, nullHypothesis="The means of the groups are equal.", dataPaired=false, dataSameSize=false, distribution=UnivariateGaussian.CDF.class, reference=@PublicationReference(author="Wikipedia",title="Ztest",type=WebPage,year=2009,url="http://en.wikipedia.org/wiki/Ztest")) public class GaussianConfidence
This test is sometimes called the "Z test" Defines a range of values that the statistic can take, as well as the confidence that the statistic is between the lower and upper bounds. This test is useful in those situations where the tested data were generated by a (univariate) Gaussian distribution.
Nested Class Summary  

static class 
GaussianConfidence.Statistic
Confidence statistics for a Gaussian distribution 
Field Summary  

static GaussianConfidence 
INSTANCE
This class has no members, so here's a static instance. 
Constructor Summary  

GaussianConfidence()
Creates a new instance of GaussianConfidence 
Method Summary  

ConfidenceInterval 
computeConfidenceInterval(Collection<? extends Number> data,
double confidence)
Computes a confidence interval for a given dataset and confidence (power) level 
ConfidenceInterval 
computeConfidenceInterval(double mean,
double variance,
int numSamples,
double confidence)
Computes the confidence interval given the mean and variance of the samples, number of samples, and corresponding confidence interval 
static ConfidenceInterval 
computeConfidenceInterval(UnivariateDistribution<?> dataDistribution,
int numSamples,
double confidence)
Computes the Gaussian confidence interval given a distribution of data, number of samples, and corresponding confidence interval 
static GaussianConfidence.Statistic 
evaluateNullHypothesis(Collection<? extends Double> data1,
double data2)
Computes the probability that the input was drawn from the estimated UnivariateGaussian distribution. 
GaussianConfidence.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 
Field Detail 

public static final GaussianConfidence INSTANCE
Constructor Detail 

public GaussianConfidence()
Method Detail 

public GaussianConfidence.Statistic evaluateNullHypothesis(Collection<? extends Number> data1, Collection<? extends Number> data2)
NullHypothesisEvaluator
evaluateNullHypothesis
in interface NullHypothesisEvaluator<Collection<? extends Number>>
data1
 First dataset to considerdata2
 Second dataset to consider
public static GaussianConfidence.Statistic evaluateNullHypothesis(Collection<? extends Double> data1, double data2)
data1
 Dataset to considerdata2
 Sample to compute the probability that a
UnivariateGaussian would produce a more unlikely sample than "data2"
public ConfidenceInterval computeConfidenceInterval(Collection<? extends Number> data, double confidence)
ConfidenceIntervalEvaluator
computeConfidenceInterval
in interface ConfidenceIntervalEvaluator<Collection<? extends Number>>
data
 Dataset to use to compute the ConfidenceIntervalconfidence
 Confidence level (power, 1pvalue) for the ConfidenceInterval,
must be on the interval (0,1]
public static ConfidenceInterval computeConfidenceInterval(UnivariateDistribution<?> dataDistribution, int numSamples, double confidence)
dataDistribution
 UnivariateGaussian describing the distribution of the underlying datanumSamples
 Number of samples in the underlying dataconfidence
 Confidence value to assume for the ConfidenceInterval
@PublicationReference(author="Wikipedia", title="Standard error (statistics)", type=WebPage, year=2009, url="http://en.wikipedia.org/wiki/Standard_error_(statistics)") public ConfidenceInterval computeConfidenceInterval(double mean, double variance, int numSamples, double confidence)
ConfidenceIntervalEvaluator
computeConfidenceInterval
in interface ConfidenceIntervalEvaluator<Collection<? extends Number>>
mean
 Mean of the distribution.variance
 Variance of the distribution.numSamples
 Number of samples in the underlying dataconfidence
 Confidence value to assume for the ConfidenceInterval


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