/** * {@inheritDoc}<p> * This implementation computes the F statistic using the definitional * formula<pre> * F = msbg/mswg</pre> * where<pre> * msbg = between group mean square * mswg = within group mean square</pre> * are as defined <a href="http://faculty.vassar.edu/lowry/ch13pt1.html"> * here</a></p> */ public double anovaFValue(Collection<double[]> categoryData) throws IllegalArgumentException, MathException { AnovaStats a = anovaStats(categoryData); return a.F; }
/** * {@inheritDoc}<p> * This implementation computes the F statistic using the definitional * formula<pre> * F = msbg/mswg</pre> * where<pre> * msbg = between group mean square * mswg = within group mean square</pre> * are as defined <a href="http://faculty.vassar.edu/lowry/ch13pt1.html"> * here</a></p> */ public double anovaFValue(Collection<double[]> categoryData) throws IllegalArgumentException, MathException { AnovaStats a = anovaStats(categoryData); return a.F; }
/** * {@inheritDoc}<p> * This implementation computes the F statistic using the definitional * formula<pre> * F = msbg/mswg</pre> * where<pre> * msbg = between group mean square * mswg = within group mean square</pre> * are as defined <a href="http://faculty.vassar.edu/lowry/ch13pt1.html"> * here</a></p> */ public double anovaFValue(Collection categoryData) throws IllegalArgumentException, MathException { AnovaStats a = anovaStats(categoryData); return a.F; }
/** * {@inheritDoc}<p> * This implementation uses the * {@link org.apache.commons.math.distribution.FDistribution * commons-math F Distribution implementation} to estimate the exact * p-value, using the formula<pre> * p = 1 - cumulativeProbability(F)</pre> * where <code>F</code> is the F value and <code>cumulativeProbability</code> * is the commons-math implementation of the F distribution.</p> */ public double anovaPValue(Collection<double[]> categoryData) throws IllegalArgumentException, MathException { AnovaStats a = anovaStats(categoryData); FDistribution fdist = new FDistributionImpl(a.dfbg, a.dfwg); return 1.0 - fdist.cumulativeProbability(a.F); }
/** * {@inheritDoc}<p> * This implementation uses the * {@link org.apache.commons.math.distribution.FDistribution * commons-math F Distribution implementation} to estimate the exact * p-value, using the formula<pre> * p = 1 - cumulativeProbability(F)</pre> * where <code>F</code> is the F value and <code>cumulativeProbability</code> * is the commons-math implementation of the F distribution.</p> */ public double anovaPValue(Collection categoryData) throws IllegalArgumentException, MathException { AnovaStats a = anovaStats(categoryData); FDistribution fdist = new FDistributionImpl(a.dfbg, a.dfwg); return 1.0 - fdist.cumulativeProbability(a.F); }
/** * {@inheritDoc}<p> * This implementation uses the * {@link org.apache.commons.math.distribution.FDistribution * commons-math F Distribution implementation} to estimate the exact * p-value, using the formula<pre> * p = 1 - cumulativeProbability(F)</pre> * where <code>F</code> is the F value and <code>cumulativeProbability</code> * is the commons-math implementation of the F distribution.</p> */ public double anovaPValue(Collection<double[]> categoryData) throws IllegalArgumentException, MathException { AnovaStats a = anovaStats(categoryData); FDistribution fdist = new FDistributionImpl(a.dfbg, a.dfwg); return 1.0 - fdist.cumulativeProbability(a.F); }