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 |
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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, toString
public 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()
AbstractCloneableSerializable
Object
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 CloneableSerializable
clone
in class AbstractCloneableSerializable
public 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