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TestResult Class
Represents the result of a statistical test.
Inheritance Hierarchy
SystemObject
  Meta.Numerics.StatisticsTestResult

Namespace:  Meta.Numerics.Statistics
Assembly:  Meta.Numerics (in Meta.Numerics.dll) Version: 3.1.0.0 (3.1.0.0)
Syntax
public class TestResult

The TestResult type exposes the following members.

Properties
  NameDescription
Public propertyDistribution
Gets the distribution of the test statistic under the null hypothesis.
Public propertyLeftProbability
Get the probability, under the null hypothesis, of obtaining a test statistic value as small or smaller than the one actually obtained.
Public propertyProbability
Gets the probability of such an extreme value of the satistic.
Public propertyRightProbability
Get the probability, under the null hypothesis, of obtaining a test statistic value as large as or larger than the one actually obtained.
Public propertyStatistic
Gets the value of the test statistic.
Public propertyType
Gets a value indicating the type of statistical test.
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Methods
  NameDescription
Public methodEquals
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as a hash function for a particular type.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Remarks

A statistical test compares a data set to a model (or to another data set) and computes a single, real number, called the test statistic, which measures how much the data set differs from model (or the other data set). The key to a useful statistical test is that the distribution of the test statistic, under the assumption that the model actually explains the data (or that the other data set is drawn from the same distribution) is known. This assumption is called the null hypothesis.

See Also