@Test public void testMinimumSampleSizeForGivenDandMaximumRisk_4args() { logger.info("minimumSampleSizeForGivenDandMaximumRisk"); double d = 0.323; double aLevel = 0.1; double populationStd = 1.7289303051309; int populationN = 7000; int expResult = 77; int result = SimpleRandomSampling.minimumSampleSizeForGivenDandMaximumRisk(d, aLevel, populationStd, populationN); assertEquals(expResult, result); }
public static int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd) { return minimumSampleSizeForGivenDandMaximumRisk(d, aLevel, populationStd, Integer.MAX_VALUE); }
SimpleRandomSampling { public static int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd) { return minimumSampleSizeForGivenDandMaximumRisk(d, aLevel, populationStd, Integer.MAX_VALUE); } }
SimpleRandomSampling { public static int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd) { return minimumSampleSizeForGivenDandMaximumRisk(d, aLevel, populationStd, Integer.MAX_VALUE); }  }
SimpleRandomSampling { public static int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd) { return minimumSampleSizeForGivenDandMaximumRisk(d, aLevel, populationStd, Integer.MAX_VALUE); }  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 int minimumSampleSizeForGivenDandMaximumRisk(double d, double aLevel, double populationStd) { return minimumSampleSizeForGivenDandMaximumRisk(d, aLevel, populationStd, Integer.MAX_VALUE); }  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);  }