org.apache.commons.math.stat.inference
Interface MannWhitneyUTest

All Known Implementing Classes:

MannWhitneyUTestImpl

public interface MannWhitneyUTest

An interface for Mann-Whitney U test (also called Wilcoxon rank-sum test).

Version:

$Id: MannWhitneyUTest.java 1131229 2011-06-03 20:49:25Z luc $

Method Summary

double	mannWhitneyU(double[] x, double[] y) Computes the Mann-Whitney U statistic comparing mean for two independent samples possibly of different length.
double	mannWhitneyUTest(double[] x, double[] y) Returns the asymptotic observed significance level, or p-value, associated with a Mann-Whitney U statistic comparing mean for two independent samples.

Method Detail

mannWhitneyU

double mannWhitneyU(double[] x,
                    double[] y)
                    throws java.lang.IllegalArgumentException

Computes the Mann-Whitney U statistic comparing mean for two independent samples possibly of different length.

This statistic can be used to perform a Mann-Whitney U test evaluating the null hypothesis that the two independent samples has equal mean.

Let X_i denote the i'th individual of the first sample and Y_j the j'th individual in the second sample. Note that the samples would often have different length.

Preconditions:

• All observations in the two samples are independent.
• The observations are at least ordinal (continuous are also ordinal).

Parameters:

x - the first sample

y - the second sample

Returns:

mannWhitneyU statistic

Throws:

java.lang.IllegalArgumentException - if preconditions are not met

mannWhitneyUTest

double mannWhitneyUTest(double[] x,
                        double[] y)
                        throws java.lang.IllegalArgumentException,
                               MathException

Returns the asymptotic observed significance level, or p-value, associated with a Mann-Whitney U statistic comparing mean for two independent samples.

Let X_i denote the i'th individual of the first sample and Y_j the j'th individual in the second sample. Note that the samples would often have different length.

Preconditions:

• All observations in the two samples are independent.
• The observations are at least ordinal (continuous are also ordinal).

Parameters:

x - the first sample

y - the second sample

Returns:

asymptotic p-value

Throws:

java.lang.IllegalArgumentException - if preconditions are not met

MathException - if an error occurs computing the p-value