com.numericalmethod.suanshu.stats.test.variance
Class F

java.lang.Object
  com.numericalmethod.suanshu.stats.test.HypothesisTest
      com.numericalmethod.suanshu.stats.test.variance.F

public class F
extends HypothesisTest

The FDistribution-test tests whether two normal populations have the same variance. This test is sensitive to the assumption that the variables are normally distributed.

The R equivalent function is var.test.

See Also:

Wikipedia: FDistribution-test of equality of variances

Field Summary

double	df1 the degree of freedoms
double	df2 the degree of freedoms
double	estimate the estimate of the ratio of two variances
UnivariateDistribution	F the associated FDistribution distribution
double	pValue1SidedGreater right, one-sided p-value
double	pValue1SidedLess left, one-sided p-value

Fields inherited from class com.numericalmethod.suanshu.stats.test.HypothesisTest

k, N, pValue, testStatistics

Constructor Summary

F(double[] sample1, double[] sample2)
Perform the FDistribution test to test for equal variance of two normal populations.

F(double[] sample1, double[] sample2, double ratio)
Perform the FDistribution test to test for equal variance of two normal populations.

Method Summary

java.lang.String	alternativeHypothesis() Get a description of the alternative hypothesis.
double[]	confidenceInterval(double confidence) Compute the confidence interval.
double	leftConfidenceInterval(double confidence) Compute the one sided left confidence interval, [0, a]
java.lang.String	nullHypothesis() Get a description of the null hypothesis.
double	rightConfidenceInterval(double confidence) Compute the one sided right confidence interval, [a, ∞)

Methods inherited from class com.numericalmethod.suanshu.stats.test.HypothesisTest

oneSidedPvalue, pValue, rejectNull, testStatistics

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

df1

public final double df1

the degree of freedoms

df2

public final double df2

the degree of freedoms

estimate

public final double estimate

the estimate of the ratio of two variances

pValue1SidedLess

public final double pValue1SidedLess

left, one-sided p-value

pValue1SidedGreater

public final double pValue1SidedGreater

right, one-sided p-value

F

public final UnivariateDistribution F

the associated FDistribution distribution

Constructor Detail

F

public F(double[] sample1,
         double[] sample2)

Perform the FDistribution test to test for equal variance of two normal populations.

Parameters:

sample1 - sample 1

sample2 - sample 2

F

public F(double[] sample1,
         double[] sample2,
         double ratio)

Perform the FDistribution test to test for equal variance of two normal populations.

Parameters:

sample1 - sample 1

sample2 - sample 2

ratio - the hypothesized ratio of the population variances of samples 1 and 2

Method Detail

nullHypothesis

public java.lang.String nullHypothesis()

Description copied from class: HypothesisTest

Get a description of the null hypothesis.

Specified by:

nullHypothesis in class HypothesisTest

Returns:

the null hypothesis description

See Also:

Wikipedia: Null hypothesis

alternativeHypothesis

public java.lang.String alternativeHypothesis()

Description copied from class: HypothesisTest

Get a description of the alternative hypothesis.

Specified by:

alternativeHypothesis in class HypothesisTest

Returns:

the alternative hypothesis description

See Also:

Wikipedia: Alternative hypothesis

confidenceInterval

public double[] confidenceInterval(double confidence)

Compute the confidence interval.

Parameters:

confidence - the confidence level, e.g., for a 2-sided 95% confidence interval, we use 0.975 because 1 - 0.95 = 2 * (1 - 0.025)

Returns:

the left and right interval values

rightConfidenceInterval

public double rightConfidenceInterval(double confidence)

Compute the one sided right confidence interval, [a, ∞)

Parameters:

confidence - the confidence level, e.g., 0.95 for 95% confidence interval

Returns:

the left interval value

leftConfidenceInterval

public double leftConfidenceInterval(double confidence)

Compute the one sided left confidence interval, [0, a]

Parameters:

confidence - the confidence level, e.g., 0.95 for 95% confidence interval

Returns:

the right interval value