Extreme Optimization™: Complexity made simple.

Math and Statistics
Libraries for .NET

  • Home
  • Features
    • Math Library
    • Vector and Matrix Library
    • Statistics Library
    • Performance
    • Usability
  • Documentation
    • Introduction
    • Math Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Reference
  • Resources
    • Downloads
    • QuickStart Samples
    • Sample Applications
    • Frequently Asked Questions
    • Technical Support
  • Blog
  • Order
  • Company
    • About us
    • Testimonials
    • Customers
    • Press Releases
    • Careers
    • Partners
    • Contact us
Introduction
Deployment Guide
Nuget packages
Configuration
Using Parallelism
Expand Mathematics Library User's GuideMathematics Library User's Guide
Expand Vector and Matrix Library User's GuideVector and Matrix Library User's Guide
Expand Data Analysis Library User's GuideData Analysis Library User's Guide
Expand Statistics Library User's GuideStatistics Library User's Guide
Expand Data Access Library User's GuideData Access Library User's Guide
Expand ReferenceReference
  • Extreme Optimization
    • Features
    • Solutions
    • Documentation
    • QuickStart Samples
    • Sample Applications
    • Downloads
    • Technical Support
    • Download trial
    • How to buy
    • Blog
    • Company
    • Resources
  • Documentation
    • Introduction
    • Deployment Guide
    • Nuget packages
    • Configuration
    • Using Parallelism
    • Mathematics Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Data Access Library User's Guide
    • Reference
  • Reference
    • Extreme
    • Extreme.Collections
    • Extreme.Data
    • Extreme.Data.Json
    • Extreme.Data.Matlab
    • Extreme.Data.R
    • Extreme.Data.Stata
    • Extreme.Data.Text
    • Extreme.DataAnalysis
    • Extreme.DataAnalysis.Linq
    • Extreme.DataAnalysis.Models
    • Extreme.Mathematics
    • Extreme.Mathematics.Algorithms
    • Extreme.Mathematics.Calculus
    • Extreme.Mathematics.Calculus.OrdinaryDifferentialEquations
    • Extreme.Mathematics.Curves
    • Extreme.Mathematics.Curves.Nonlinear
    • Extreme.Mathematics.Distributed
    • Extreme.Mathematics.EquationSolvers
    • Extreme.Mathematics.Generic
    • Extreme.Mathematics.LinearAlgebra
    • Extreme.Mathematics.LinearAlgebra.Implementation
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers.Preconditioners
    • Extreme.Mathematics.Optimization
    • Extreme.Mathematics.Optimization.LineSearches
    • Extreme.Mathematics.Random
    • Extreme.Mathematics.SignalProcessing
    • Extreme.Providers
    • Extreme.Providers.InteropServices
    • Extreme.Statistics
    • Extreme.Statistics.Distributions
    • Extreme.Statistics.Multivariate
    • Extreme.Statistics.Tests
    • Extreme.Statistics.TimeSeriesAnalysis
  • Extreme.Statistics.Tests
    • AndersonDarlingDistribution Class
    • AndersonDarlingTest Class
    • AnovaPostHocTest Class
    • BartlettTest Class
    • ChiSquareGoodnessOfFitTest Class
    • Exactness Enumeration
    • FTest Class
    • GeneralizedEsdTest Class
    • GrubbsTest Class
    • HypothesisTest Class
    • HypothesisType Enumeration
    • KruskalWallisTest Class
    • LeveneTest Class
    • LeveneTestLocationMeasure Enumeration
    • LjungBoxTest Class
    • MannWhitneyTest(T) Class
    • McNemarTest Class
    • MultiSampleTest(T) Class
    • OneSampleChiSquareTest Class
    • OneSampleKolmogorovSmirnovTest Class
    • OneSampleTest Class
    • OneSampleTest(T) Class
    • OneSampleTTest Class
    • OneSampleZTest Class
    • OneSampleZTestOfProportion Class
    • RunsTest(T) Class
    • SamplePairing Enumeration
    • ShapiroWilkTest Class
    • SimpleHypothesisTest Class
    • StuartMaxwellTest Class
    • StudentizedRangeDistribution Class
    • TwoSampleKolmogorovSmirnovTest Class
    • TwoSampleTest Class
    • TwoSampleTest(T) Class
    • TwoSampleTTest Class
    • TwoSampleZTest Class
  • LeveneTest Class
    • LeveneTest Constructors
    • Properties
    • LeveneTest Methods

LeveneTest Class

Extreme Optimization Numerical Libraries for .NET Professional
Represents Levene's test that a set of samples have the same variance.
Inheritance Hierarchy

SystemObject
  Extreme.Statistics.TestsHypothesisTest
    Extreme.Statistics.TestsMultiSampleTestDouble
      Extreme.Statistics.TestsLeveneTest

Namespace:  Extreme.Statistics.Tests
Assembly:  Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
Syntax

C#
VB
C++
F#
Copy
public sealed class LeveneTest : MultiSampleTest<double>
Public NotInheritable Class LeveneTest
	Inherits MultiSampleTest(Of Double)
public ref class LeveneTest sealed : public MultiSampleTest<double>
[<SealedAttribute>]
type LeveneTest =  
    class
        inherit MultiSampleTest<float>
    end

The LeveneTest type exposes the following members.

Constructors

  NameDescription
Public methodLeveneTest
Constructs a new LeveneTest.
Public methodLeveneTest(IDataFrame)
Constructs a new LeveneTest for the samples in a data frame.
Public methodLeveneTest(VectorDouble)
Constructs a new LeveneTest for the specified vector array.
Public methodLeveneTest(IDataFrame, LeveneTestLocationMeasure)
Constructs a new LeveneTest for the samples in a data frame.
Public methodLeveneTest(VectorDouble, IGrouping)
Constructs a new LeveneTest for the specified vector array.
Public methodLeveneTest(VectorDouble, LeveneTestLocationMeasure)
Constructs a new LeveneTest for the specified vector array.
Public methodLeveneTest(VectorDouble, IGrouping, LeveneTestLocationMeasure)
Constructs a new LeveneTest for the specified vector array.
Top
Properties

  NameDescription
Public propertyDenominatorDegreesOfFreedom
Gets the degrees of freedom of the sample in the denominator of the F distribution.
Public propertyDistribution
Gets the probability distribution used in the hypothesis test.
(Inherited from HypothesisTest.)
Public propertyGrouping
Gets the grouping that divides Sample into groups.
(Inherited from MultiSampleTestT.)
Public propertyHypothesisType
Gets or sets whether the test is one or two-tailed.
(Inherited from HypothesisTest.)
Public propertyLocationMeasure
Gets or sets the location measure used by this LeveneTest.
Public propertyName
Gets the name of the hypothesis test.
(Overrides HypothesisTestName.)
Public propertyNumeratorDegreesOfFreedom
Gets the degrees of freedom of the sample in the numerator of the F distribution.
Public propertyPValue
Gets the probability that the test statistic would take on the calculated value under the alternate hypothesis.
(Inherited from HypothesisTest.)
Public propertySample
Gets the vector that contains the sample data.
(Inherited from MultiSampleTestT.)
Public propertySamples
Gets the collection of samples for the test.
(Inherited from MultiSampleTestT.)
Public propertySignificanceLevel
Gets the significance level used to test the null hypothesis.
(Inherited from HypothesisTest.)
Public propertyStatistic
Gets the value of the test statistic.
(Inherited from HypothesisTest.)
Top
Methods

  NameDescription
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Public methodGetConfidenceInterval
Returns the confidence interval for the test parameter for the default confidence level.
(Inherited from HypothesisTest.)
Public methodGetConfidenceInterval(Double)
Returns the confidence interval for the test parameter for the specified confidence level.
(Inherited from HypothesisTest.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetLowerCriticalValue
Gets the lower critical value for the hypothesis test's current significance level.
(Inherited from HypothesisTest.)
Public methodGetLowerCriticalValue(Double)
Gets the lower critical value for the hypothesis test at the specified significance level.
(Inherited from HypothesisTest.)
Public methodGetPValue
Gets the probability that the test statistic would take on the calculated value under the specified alternate hypothesis.
(Inherited from HypothesisTest.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodGetUpperCriticalValue
Gets the upper critical value for the test statistic at the hypothesis test's current significance level.
(Inherited from HypothesisTest.)
Public methodGetUpperCriticalValue(Double)
Gets the upper critical value for the test statistic at the specified significance level.
(Inherited from HypothesisTest.)
Public methodReject
Returns whether the null hypothesis is rejected using the default significance level.
(Inherited from HypothesisTest.)
Public methodReject(Double)
Returns whether the null hypothesis is rejected using the specified significance level.
(Inherited from HypothesisTest.)
Public methodSummarize
Returns a string containing a human-readable summary of the object.
(Inherited from HypothesisTest.)
Public methodSummarize(SummaryOptions)
Returns a string containing a human-readable summary of the object using the specified options.
(Inherited from HypothesisTest.)
Public methodToString
Returns a string that represents the current object.
(Inherited from HypothesisTest.)
Top
Remarks

Use the LeveneTest class to test whether a number of samples have the same variance. This property is called homogeneity of variance.

Some statistical procedures, such as the Analysis of Variance, assume that variances are the same across groups.

Bartlett's test can also be used for this purpose. However, Levene's test is more robust against departures from normality. On the down side, Levene's test is slower than Bartlett's test. If there is strong evidence that the data is, in fact, distributed normally, then Bartlett's test is usually preferred.

See Also

Reference

Extreme.Statistics.Tests Namespace
Extreme.Statistics.TestsBartlettTest

Copyright (c) 2004-2021 ExoAnalytics Inc.

Send comments on this topic to support@extremeoptimization.com

Copyright © 2004-2021, Extreme Optimization. All rights reserved.
Extreme Optimization, Complexity made simple, M#, and M Sharp are trademarks of ExoAnalytics Inc.
Microsoft, Visual C#, Visual Basic, Visual Studio, Visual Studio.NET, and the Optimized for Visual Studio logo
are registered trademarks of Microsoft Corporation.