public sealed class AndersonDarlingTest : OneSampleTest

Public NotInheritable Class AndersonDarlingTest
	Inherits OneSampleTest

public ref class AndersonDarlingTest sealed : public OneSampleTest

[<SealedAttribute>]
type AndersonDarlingTest =  
    class
        inherit OneSampleTest
    end

The AndersonDarlingTest type exposes the following members.

	Name	Description
	AndersonDarlingTest	Constructs a new Anderson-Darling test of normality.
	AndersonDarlingTest(NumericalVariable)	Constructs a new Anderson-Darling test of normality.
	AndersonDarlingTest(VectorDouble)	Constructs a new Anderson-Darling test of normality.
	AndersonDarlingTest(VectorDouble, ContinuousDistribution)	Constructs a new Anderson-Darling test for the specified distribution.
	AndersonDarlingTest(NumericalVariable, Double, Double)	Constructs a new Anderson-Darling test of normality.
	AndersonDarlingTest(VectorDouble, Double, Double)	Constructs a new Anderson-Darling test of normality.

	Name	Description
	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.)
	Mean	Gets or sets the mean of the distribution being tested.
	Name	Gets the name of the hypothesis test. (Overrides HypothesisTestName.)
	PValue	Gets the probability that the test statistic would take on the calculated value under the alternate hypothesis. (Inherited from HypothesisTest.)
	Sample	Gets or sets the variable the test is to be applied to. (Inherited from OneSampleTestT.)
	SignificanceLevel	Gets the significance level used to test the null hypothesis. (Inherited from HypothesisTest.)
	StandardDeviation	Gets or sets the standard deviation of the distribution being tested.
	Statistic	Gets the value of the test statistic. (Inherited from HypothesisTest.)

	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 a hash function for a particular type. (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. (Overrides HypothesisTestSummarize(SummaryOptions).)
	ToString	Returns a string that represents the current object. (Inherited from Object.)
	ToString	Returns a string that represents the current object. (Inherited from HypothesisTest.)

Use the AndersonDarlingTest class to test whether a sample comes from a normal distribution. The Anderson-Darling test is a variation of the Kolmogorov-Smirnov test that gives more weight to the tails of the distribution. In addition, the parameters of the distribution may be estimated from the sample. This makes the test more applicable in a larger number of cases.

The Mean and StandardDeviation of the distribution may be specified, but this is not necessary.

Numerical Libraries

Reference