@Test public void testVariance() { logger.info("variance"); FlatDataCollection flatDataCollection = generateFlatDataCollection(); double expResult = 52.621426666667; double result = SimpleRandomSampling.variance(flatDataCollection); assertEquals(expResult, result, Constants.DOUBLE_ACCURACY_HIGH); }
public static double variance(FlatDataCollection flatDataCollection) { return Descriptives.variance(flatDataCollection,true); }
SimpleRandomSampling { public static double variance(FlatDataCollection flatDataCollection) { return Descriptives.variance(flatDataCollection,true); } }
SimpleRandomSampling { public static double variance(FlatDataCollection flatDataCollection) { return Descriptives.variance(flatDataCollection,true); }  }
SimpleRandomSampling { public static double variance(FlatDataCollection flatDataCollection) { return Descriptives.variance(flatDataCollection,true); }  static FlatDataCollection weightedSampling(AssociativeArray weightedTable, int n, boolean withReplacement); static FlatDataCollection randomSampling(FlatDataList idList, int n, boolean withReplacement); static double mean(FlatDataCollection flatDataCollection); static double variance(FlatDataCollection flatDataCollection); static double std(FlatDataCollection flatDataCollection); static double xbarVariance(double variance, int sampleN); static double xbarVariance(double variance, int sampleN, int populationN); static double xbarStd(double std, int sampleN); static double xbarStd(double std, int sampleN, int populationN); static double pbarVariance(double pbar, int sampleN); static double pbarVariance(double pbar, int sampleN, int populationN); static double pbarStd(double pbar, int sampleN); static double pbarStd(double pbar, int sampleN, int populationN); static int minimumSampleSizeForMaximumXbarStd(double maximumXbarStd, double populationStd); static int minimumSampleSizeForMaximumXbarStd(double maximumXbarStd, double populationStd, int populationN); static int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd); static int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd, int populationN); }
SimpleRandomSampling { public static double variance(FlatDataCollection flatDataCollection) { return Descriptives.variance(flatDataCollection,true); }  static FlatDataCollection weightedSampling(AssociativeArray weightedTable, int n, boolean withReplacement); static FlatDataCollection randomSampling(FlatDataList idList, int n, boolean withReplacement); static double mean(FlatDataCollection flatDataCollection); static double variance(FlatDataCollection flatDataCollection); static double std(FlatDataCollection flatDataCollection); static double xbarVariance(double variance, int sampleN); static double xbarVariance(double variance, int sampleN, int populationN); static double xbarStd(double std, int sampleN); static double xbarStd(double std, int sampleN, int populationN); static double pbarVariance(double pbar, int sampleN); static double pbarVariance(double pbar, int sampleN, int populationN); static double pbarStd(double pbar, int sampleN); static double pbarStd(double pbar, int sampleN, int populationN); static int minimumSampleSizeForMaximumXbarStd(double maximumXbarStd, double populationStd); static int minimumSampleSizeForMaximumXbarStd(double maximumXbarStd, double populationStd, int populationN); static int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd); static int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd, int populationN);  }