def confidenceInterval(data, confidence):
PopulationSampling._checkList(data)
mean = DescriptiveStatistics.mean(data)
se = scipy.stats.sem(data)
i = se * PopulationSampling.tscore(len(data), confidence)
return [mean, mean - i, mean + i]
def test_stdev(self): self.assertAlmostEqual(277.78211542, DescriptiveStatistics.stdev(self.testdata))
def test_mode_multiple(self): data = [1, 7, 4, 7, 2, 8, 4] self.assertEqual([4, 7], DescriptiveStatistics.mode(data))
def test_mode_single(self): data = [1, 7, 4, 7, 2, 8] self.assertEqual([7], DescriptiveStatistics.mode(data))
def mode(self, data): self.result = DescriptiveStatistics.mode(data) return self.result
def test_meanDeviation(self): self.assertAlmostEqual(214.16539738, DescriptiveStatistics.meanDeviation(self.testdata))
def test_skewness(self): self.assertAlmostEqual(0.17767941, DescriptiveStatistics.skewness(self.testdata))
def test_pcovariance(self): data1 = [14.2, 16.4, 11.9, 15.2, 18.5] data2 = [215, 325, 185, 332, 406] self.assertEqual(169.156, DescriptiveStatistics.pcovariance(data1, data2))
def sampleCorrelation(self, data1, data2): self.result = DescriptiveStatistics.sampleCorrelation(data1, data2) return self.result
def meanDeviation(self, data): self.result = DescriptiveStatistics.meanDeviation(data) return self.result
def zscore(self, value, mean, stdev): self.result = DescriptiveStatistics.zscore(value, mean, stdev) return self.result
def skewness(self, data): self.result = DescriptiveStatistics.skewness(data) return self.result
def quartiles(self, data): self.result = DescriptiveStatistics.quartiles(self.testdata) return self.result
def variance(self, data): self.result = DescriptiveStatistics.variance(data) return self.result
def stdev(self, data): self.result = DescriptiveStatistics.stdev(data) return self.result
def test_pstdev(self): self.assertAlmostEqual(270.74851517, DescriptiveStatistics.pstdev(self.testdata))
def test_variance(self): self.assertAlmostEqual(77162.90365125, DescriptiveStatistics.variance(self.testdata))
def populationCorrelation(self, data1, data2): self.result = DescriptiveStatistics.populationCorrelation(data, data2) return self.result
def test_quartiles(self): self.assertEqual([168.01569232654998, 390.26554121388835, 557.6497868225864], DescriptiveStatistics.quartiles(self.testdata))
def test_mean(self): self.assertAlmostEqual(406.71759600, DescriptiveStatistics.mean(self.testdata))
def test_zscore(self): value = 1100 mean = 1026 stdev = 209 self.assertAlmostEqual(0.35406698, DescriptiveStatistics.zscore(value, mean, stdev))
def test_median(self): self.assertAlmostEqual(390.26554121, DescriptiveStatistics.median(self.testdata))
def test_population_correlation(self): data1 = [14.2, 16.4, 11.9, 15.2, 18.5] data2 = [215, 325, 185, 332, 406] self.assertAlmostEqual(0.94532854, DescriptiveStatistics.populationCorrelation(data1, data2))
def median(self, data): self.result = DescriptiveStatistics.median(data) return self.result