• 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
• TwoSampleZTest Class
  • TwoSampleZTest Constructors
  • Properties
  • TwoSampleZTest Methods

TwoSampleZTest Class

Extreme Optimization Numerical Libraries for .NET Professional

Represents a test that the difference between two proportions of independent samples is significant.

Inheritance Hierarchy

---

SystemObject
  Extreme.Statistics.TestsHypothesisTest
    Extreme.Statistics.TestsTwoSampleZTest

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

Syntax

---

C#

VB

C++

F#

Copy

public sealed class TwoSampleZTest : HypothesisTest

Public NotInheritable Class TwoSampleZTest
	Inherits HypothesisTest

public ref class TwoSampleZTest sealed : public HypothesisTest

[<SealedAttribute>]
type TwoSampleZTest =  
    class
        inherit HypothesisTest
    end

The TwoSampleZTest type exposes the following members.

Constructors

---

	Name	Description
	TwoSampleZTest	Constructs a new unpaired TwoSampleZTest for the specified samples.
	TwoSampleZTest(Int32, Double, Int32, Double, Double, HypothesisType)	Constructs a new TwoSampleZTest for the specified samples.

Top

Properties

---

	Name	Description
	Count1	Gets or sets the number of observations of the first sample.
	Count2	Gets or sets the number of observations of the second sample.
	Difference	Gets or sets the proposed difference between the two means.
	Distribution	Gets the probability distribution used in the hypothesis test. (Inherited from HypothesisTest.)
	HypothesisType	Gets or sets whether the test is one or two-tailed. (Inherited from HypothesisTest.)
	Name	Gets the name of the hypothesis test. (Overrides HypothesisTestName.)
	Proportion1	Gets or sets the proportion for the first sample.
	Proportion2	Gets or sets the proportion for the second sample.
	PValue	Gets the probability that the test statistic would take on the calculated value under the alternate hypothesis. (Inherited from HypothesisTest.)
	SignificanceLevel	Gets the significance level used to test the null hypothesis. (Inherited from HypothesisTest.)
	Statistic	Gets the value of the test statistic. (Inherited from HypothesisTest.)

Top

Methods

---

	Name	Description
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	GetConfidenceInterval	Returns the confidence interval for the test parameter for the default confidence level. (Inherited from HypothesisTest.)
	GetConfidenceInterval(Double)	Returns the confidence interval for the test parameter for the specified confidence level. (Inherited from HypothesisTest.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetLowerCriticalValue	Gets the lower critical value for the hypothesis test's current significance level. (Inherited from HypothesisTest.)
	GetLowerCriticalValue(Double)	Gets the lower critical value for the hypothesis test at the specified significance level. (Inherited from HypothesisTest.)
	GetPValue	Gets the probability that the test statistic would take on the calculated value under the specified alternate hypothesis. (Inherited from HypothesisTest.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	GetUpperCriticalValue	Gets the upper critical value for the test statistic at the hypothesis test's current significance level. (Inherited from HypothesisTest.)
	GetUpperCriticalValue(Double)	Gets the upper critical value for the test statistic at the specified significance level. (Inherited from HypothesisTest.)
	Reject	Returns whether the null hypothesis is rejected using the default significance level. (Inherited from HypothesisTest.)
	Reject(Double)	Returns whether the null hypothesis is rejected using the specified significance level. (Inherited from HypothesisTest.)
	Summarize	Returns a string containing a human-readable summary of the object. (Inherited from HypothesisTest.)
	Summarize(SummaryOptions)	Returns a string containing a human-readable summary of the object using the specified options. (Inherited from HypothesisTest.)
	ToString	Returns a string that represents the current object. (Inherited from HypothesisTest.)

Top

Remarks

---

Use the TwoSampleZTest class to test the hypothesis that the difference between proportions of independent samples is significant.

See Also

---

Reference

Extreme.Statistics.Tests Namespace

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.