org.apache.commons.math.stat.inference

Interface OneWayAnova

All Known Implementing Classes:

OneWayAnovaImpl

public interface OneWayAnova

An interface for one-way ANOVA (analysis of variance).

Tests for differences between two or more categories of univariate data (for example, the body mass index of accountants, lawyers, doctors and computer programmers). When two categories are given, this is equivalent to the TTest.

Since:

1.2

Method Summary

Modifier and Type	Method and Description
double	anovaFValue(java.util.Collection<double[]> categoryData) Computes the ANOVA F-value for a collection of double[] arrays.
double	anovaPValue(java.util.Collection<double[]> categoryData) Computes the ANOVA P-value for a collection of double[] arrays.
boolean	anovaTest(java.util.Collection<double[]> categoryData, double alpha) Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.

Method Detail

anovaFValue

double anovaFValue(java.util.Collection<double[]> categoryData)
            throws java.lang.IllegalArgumentException,
                   MathException

Computes the ANOVA F-value for a collection of double[] arrays.

Preconditions:

• The categoryData Collection must contain double[] arrays.
• There must be at least two double[] arrays in the categoryData collection and each of these arrays must contain at least two values.

Parameters:

categoryData - Collection of double[] arrays each containing data for one category

Returns:

Fvalue

Throws:

java.lang.IllegalArgumentException - if the preconditions are not met

MathException - if the statistic can not be computed do to a convergence or other numerical error.

anovaPValue

double anovaPValue(java.util.Collection<double[]> categoryData)
            throws java.lang.IllegalArgumentException,
                   MathException

Computes the ANOVA P-value for a collection of double[] arrays.

Preconditions:

• The categoryData Collection must contain double[] arrays.
• There must be at least two double[] arrays in the categoryData collection and each of these arrays must contain at least two values.

Parameters:

categoryData - Collection of double[] arrays each containing data for one category

Returns:

Pvalue

Throws:

java.lang.IllegalArgumentException - if the preconditions are not met

MathException - if the statistic can not be computed do to a convergence or other numerical error.

anovaTest

boolean anovaTest(java.util.Collection<double[]> categoryData,
                  double alpha)
           throws java.lang.IllegalArgumentException,
                  MathException

Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.

Preconditions:

• The categoryData Collection must contain double[] arrays.
• There must be at least two double[] arrays in the categoryData collection and each of these arrays must contain at least two values.
• alpha must be strictly greater than 0 and less than or equal to 0.5.

Parameters:

categoryData - Collection of double[] arrays each containing data for one category

alpha - significance level of the test

Returns:

true if the null hypothesis can be rejected with confidence 1 - alpha

Throws:

java.lang.IllegalArgumentException - if the preconditions are not met

MathException - if the statistic can not be computed do to a convergence or other numerical error.