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import unittest |
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from random import random |
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from numpy.random.mtrand import normal |
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from pysie.dsl.one_group import MeanTesting, ProportionTesting |
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from pysie.stats.distributions import MeanSamplingDistribution, ProportionSamplingDistribution |
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from pysie.stats.samples import Sample, SampleDistribution |
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10
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class MeanTestingUnitTest(unittest.TestCase): |
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def test_mean_normal(self): |
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mu = 0.0 |
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sigma = 1.0 |
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sample_size = 31 |
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sample = Sample() |
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for i in range(sample_size): |
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sample.add_numeric(normal(mu, sigma)) |
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sampling_distribution = MeanSamplingDistribution(sample_distribution=SampleDistribution(sample)) |
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testing = MeanTesting(sampling_distribution=sampling_distribution, mean_null=0.0) |
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print('one tail p-value: ' + str(testing.p_value_one_tail)) |
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print('two tail p-value: ' + str(testing.p_value_two_tail)) |
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reject_one_tail, reject_two_tail = testing.will_reject(0.01) |
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print('will reject mean = 0 (one-tail) ? ' + str(reject_one_tail)) |
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print('will reject mean = 0 (two-tail) ? ' + str(reject_two_tail)) |
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self.assertFalse(reject_one_tail) |
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self.assertFalse(reject_two_tail) |
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32
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def test_mean_student(self): |
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mu = 0.0 |
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sigma = 1.0 |
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sample_size = 29 |
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sample = Sample() |
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for i in range(sample_size): |
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sample.add_numeric(normal(mu, sigma)) |
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sampling_distribution = MeanSamplingDistribution(sample_distribution=SampleDistribution(sample)) |
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testing = MeanTesting(sampling_distribution=sampling_distribution, mean_null=0.0) |
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print('one tail p-value: ' + str(testing.p_value_one_tail)) |
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print('two tail p-value: ' + str(testing.p_value_two_tail)) |
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reject_one_tail, reject_two_tail = testing.will_reject(0.01) |
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print('will reject mean = 0 (one-tail) ? ' + str(reject_one_tail)) |
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print('will reject mean = 0 (two-tail) ? ' + str(reject_two_tail)) |
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self.assertFalse(reject_one_tail) |
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self.assertFalse(reject_two_tail) |
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52
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class ProportionTestingUnitTest(unittest.TestCase): |
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View Code Duplication |
def test_proportion_normal(self): |
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sample = Sample() |
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for i in range(100): |
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if random() <= 0.6: |
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sample.add_category("OK") |
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else: |
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sample.add_category("CANCEL") |
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sampling_distribution = ProportionSamplingDistribution( |
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sample_distribution=SampleDistribution(sample, categorical_value="OK")) |
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testing = ProportionTesting(sampling_distribution=sampling_distribution, p_null=0.6) |
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print('one tail p-value: ' + str(testing.p_value_one_tail)) |
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print('two tail p-value: ' + str(testing.p_value_two_tail)) |
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reject_one_tail, reject_two_tail = testing.will_reject(0.01) |
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print('will reject p = 0.6 (one-tail) ? ' + str(reject_one_tail)) |
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print('will reject p = 0.6 (two-tail) ? ' + str(reject_two_tail)) |
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self.assertFalse(reject_one_tail) |
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self.assertFalse(reject_two_tail) |
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76
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View Code Duplication |
def test_proportion_simulation(self): |
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77
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sample = Sample() |
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for i in range(10): |
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if random() <= 0.6: |
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sample.add_category("OK") |
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else: |
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sample.add_category("CANCEL") |
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sampling_distribution = ProportionSamplingDistribution( |
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sample_distribution=SampleDistribution(sample, categorical_value="OK")) |
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testing = ProportionTesting(sampling_distribution=sampling_distribution, p_null=0.6) |
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print('one tail p-value: ' + str(testing.p_value_one_tail)) |
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print('two tail p-value: ' + str(testing.p_value_two_tail)) |
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reject_one_tail, reject_two_tail = testing.will_reject(0.01) |
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print('will reject p = 0.6 (one-tail) ? ' + str(reject_one_tail)) |
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print('will reject p = 0.6 (two-tail) ? ' + str(reject_two_tail)) |
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self.assertFalse(reject_one_tail) |
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self.assertFalse(reject_two_tail) |
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98
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if __name__ == '__main__': |
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unittest.main() |
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chen0040 /
pysie
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