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Kirill Smelkov
cpython
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00305ade
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00305ade
authored
8 years ago
by
Raymond Hettinger
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Add another example to the recipes section of the random docs
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@@ -372,3 +372,29 @@ sample of size five::
print(f'The sample mean of {mean(data):.1f} has a 90% confidence '
f'interval from {means[1]:.1f} to {means[-2]:.1f}')
Example of a `resampling permutation test
<https://en.wikipedia.org/wiki/Resampling_(statistics)#Permutation_tests>`_
to determine the statistical significance or `p-value
<https://en.wikipedia.org/wiki/P-value>`_ of an observed difference
between the effects of a drug versus a placebo::
# Example from "Statistics is Easy" by Dennis Shasha and Manda Wilson
from statistics import mean
from random import shuffle
drug = [54, 73, 53, 70, 73, 68, 52, 65, 65]
placebo = [54, 51, 58, 44, 55, 52, 42, 47, 58, 46]
observed_diff = mean(drug) - mean(placebo)
n = 10000
count = 0
combined = drug + placebo
for i in range(n):
shuffle(combined)
new_diff = mean(combined[:len(drug)]) - mean(combined[len(drug):])
count += (new_diff >= observed_diff)
print(f'{n} label reshufflings produced only {count} instances with a difference')
print(f'at least as extreme as the observed difference of {observed_diff:.1f}.')
print(f'The one-sided p-value of {count / n:.4f} leads us to reject the null')
print(f'hypothesis that the observed difference occurred due to chance.')
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