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@@ 100-114 (lines=15) @@
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| 97 |
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for i in range(grp2_sample_size): |
| 98 |
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grp2_sample.add_numeric(normal(grp2_mu, grp2_sigma)) |
| 99 |
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| 100 |
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sampling_distribution = MeanDiffSamplingDistribution(grp1_sample_distribution=SampleDistribution(grp1_sample), |
| 101 |
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grp2_sample_distribution=SampleDistribution(grp2_sample)) |
| 102 |
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self.assertEqual(sampling_distribution.distribution_family, DistributionFamily.normal) |
| 103 |
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print('sampling distribution: (point_estimate = ' + str(sampling_distribution.point_estimate) |
| 104 |
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+ ', standard_error = ' + str(sampling_distribution.standard_error) + ')') |
| 105 |
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print('confidence interval for 95% confidence level: ' + str(sampling_distribution.confidence_interval(0.95))) |
| 106 |
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| 107 |
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def test_confidence_interval_with_sample_stats_student(self): |
| 108 |
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grp1_sample_mean = 0 |
| 109 |
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grp1_sample_sd = 1 |
| 110 |
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grp1_sample_size = 29 |
| 111 |
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grp2_sample_mean = 0.001 |
| 112 |
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grp2_sample_sd = 1.3 |
| 113 |
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grp2_sample_size = 24 |
| 114 |
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sampling_distribution = MeanDiffSamplingDistribution(grp1_sample_mean=grp1_sample_mean, |
| 115 |
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grp1_sample_sd=grp1_sample_sd, |
| 116 |
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grp1_sample_size=grp1_sample_size, |
| 117 |
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grp2_sample_mean=grp2_sample_mean, |
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@@ 74-88 (lines=15) @@
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| 71 |
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grp2_sample_size = 36 |
| 72 |
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sampling_distribution = MeanDiffSamplingDistribution(grp1_sample_mean=grp1_sample_mean, |
| 73 |
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grp1_sample_sd=grp1_sample_sd, |
| 74 |
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grp1_sample_size=grp1_sample_size, |
| 75 |
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grp2_sample_mean=grp2_sample_mean, |
| 76 |
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grp2_sample_sd=grp2_sample_sd, |
| 77 |
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grp2_sample_size=grp2_sample_size) |
| 78 |
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self.assertEqual(sampling_distribution.distribution_family, DistributionFamily.normal) |
| 79 |
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print('sampling distribution: (point_estimate = ' + str(sampling_distribution.point_estimate) |
| 80 |
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+ ', standard_error=' + str(sampling_distribution.standard_error) + ')') |
| 81 |
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print('confidence interval for 95% confidence level: ' + str(sampling_distribution.confidence_interval(0.95))) |
| 82 |
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| 83 |
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def test_confidence_interval_with_sample_normal(self): |
| 84 |
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grp1_mu = 0.0 |
| 85 |
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grp1_sigma = 1.0 |
| 86 |
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grp1_sample_size = 31 |
| 87 |
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grp1_sample = Sample() |
| 88 |
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| 89 |
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grp2_mu = 0.09 |
| 90 |
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grp2_sigma = 2.0 |
| 91 |
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grp2_sample_size = 36 |
chen0040 /
pysie
