public static class StudentTConfidence.Statistic extends AbstractConfidenceStatistic
nullHypothesisProbability| Constructor and Description |
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Statistic(double t,
double degreesOfFreedom)
Creates a new instance of Statistic
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Statistic(StudentTConfidence.Statistic other)
Copy Constructor
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| Modifier and Type | Method and Description |
|---|---|
StudentTConfidence.Statistic |
clone()
This makes public the clone method on the
Object class and
removes the exception that it throws. |
double |
getDegreesOfFreedom()
Getter for degreesOfFreedom
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double |
getT()
Getter for t
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double |
getTestStatistic()
Gets the statistic from which we compute the null-hypothesis probability.
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protected void |
setDegreesOfFreedom(double degreesOfFreedom)
Setter for degreesOfFreedom
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protected void |
setT(double t)
Setter for t
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static double |
twoTailTStatistic(double t,
double degreesOfFreedom)
Computes the likelihood that a StudentTDistribution would generate
a LESS LIKELY sample as "t", given the degrees of freedom.
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getNullHypothesisProbability, setNullHypothesisProbability, toStringpublic Statistic(double t,
double degreesOfFreedom)
t - Value that is used in the Student-t CDF to compute the probability.
Usually just called the "t-statistic"degreesOfFreedom - Number of degrees of freedom in the Student-t distribution, usually
the number of data points - 1public Statistic(StudentTConfidence.Statistic other)
other - Statistic to copypublic StudentTConfidence.Statistic clone()
AbstractCloneableSerializableObject class and
removes the exception that it throws. Its default behavior is to
automatically create a clone of the exact type of object that the
clone is called on and to copy all primitives but to keep all references,
which means it is a shallow copy.
Extensions of this class may want to override this method (but call
super.clone() to implement a "smart copy". That is, to target
the most common use case for creating a copy of the object. Because of
the default behavior being a shallow copy, extending classes only need
to handle fields that need to have a deeper copy (or those that need to
be reset). Some of the methods in ObjectUtil may be helpful in
implementing a custom clone method.
Note: The contract of this method is that you must use
super.clone() as the basis for your implementation.clone in interface CloneableSerializableclone in class AbstractCloneableSerializablepublic static double twoTailTStatistic(double t,
double degreesOfFreedom)
t - Sample to determine how likely a worse sample is than "t"degreesOfFreedom - Number of degrees of freedom in the Student-t distributionpublic double getT()
protected void setT(double t)
t - Value that is used in the Student-t CDF to compute the probability.
Usually just called the "t-statistic"public double getDegreesOfFreedom()
protected void setDegreesOfFreedom(double degreesOfFreedom)
degreesOfFreedom - Number of degrees of freedom in the Student-t distribution, usually
the number of data points - 1public double getTestStatistic()
ConfidenceStatistic