@Test public void testMean() { logger.info("mean"); TransposeDataCollection sampleDataCollection = generateSampleDataCollection(); double expResult = 17.5; double result = ClusterSampling.mean(sampleDataCollection); assertEquals(expResult, result, Constants.DOUBLE_ACCURACY_HIGH); }
public static double mean(TransposeDataCollection sampleDataCollection) { double mean = 0.0; int totalSampleN = 0; for(Map.Entry<Object, FlatDataCollection> entry : sampleDataCollection.entrySet()) { mean += Descriptives.sum(entry.getValue()); totalSampleN += entry.getValue().size(); } mean/=totalSampleN; return mean; }
ClusterSampling { public static double mean(TransposeDataCollection sampleDataCollection) { double mean = 0.0; int totalSampleN = 0; for(Map.Entry<Object, FlatDataCollection> entry : sampleDataCollection.entrySet()) { mean += Descriptives.sum(entry.getValue()); totalSampleN += entry.getValue().size(); } mean/=totalSampleN; return mean; } }
ClusterSampling { public static double mean(TransposeDataCollection sampleDataCollection) { double mean = 0.0; int totalSampleN = 0; for(Map.Entry<Object, FlatDataCollection> entry : sampleDataCollection.entrySet()) { mean += Descriptives.sum(entry.getValue()); totalSampleN += entry.getValue().size(); } mean/=totalSampleN; return mean; }  }
ClusterSampling { public static double mean(TransposeDataCollection sampleDataCollection) { double mean = 0.0; int totalSampleN = 0; for(Map.Entry<Object, FlatDataCollection> entry : sampleDataCollection.entrySet()) { mean += Descriptives.sum(entry.getValue()); totalSampleN += entry.getValue().size(); } mean/=totalSampleN; return mean; }  static double nBar(TransposeDataList clusterIdList); static TransposeDataCollection randomSampling(TransposeDataList clusterIdList, int sampleM); static double mean(TransposeDataCollection sampleDataCollection); static double xbarVariance(TransposeDataCollection sampleDataCollection, int populationM, double Nbar); static double xbarStd(TransposeDataCollection sampleDataCollection, int populationM, double Nbar); }
ClusterSampling { public static double mean(TransposeDataCollection sampleDataCollection) { double mean = 0.0; int totalSampleN = 0; for(Map.Entry<Object, FlatDataCollection> entry : sampleDataCollection.entrySet()) { mean += Descriptives.sum(entry.getValue()); totalSampleN += entry.getValue().size(); } mean/=totalSampleN; return mean; }  static double nBar(TransposeDataList clusterIdList); static TransposeDataCollection randomSampling(TransposeDataList clusterIdList, int sampleM); static double mean(TransposeDataCollection sampleDataCollection); static double xbarVariance(TransposeDataCollection sampleDataCollection, int populationM, double Nbar); static double xbarStd(TransposeDataCollection sampleDataCollection, int populationM, double Nbar);  }