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Add cum_weights example (simulation of a cumulative binomial distribution).

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Raymond Hettinger 2016-10-20 01:36:52 -07:00
parent 812f6e1f23
commit 24f33b5bb5
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7
Doc/library/random.rst
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@ -351,6 +351,13 @@ Basic usage::
>>> choices(['red', 'black', 'green'], [18, 18, 2], k=6)
['red', 'green', 'black', 'black', 'red', 'black']
# Probability of getting 5 or more heads from 7 spins of a biased coin
# that settles on heads 60% of the time.
>>> n = 10000
>>> cw = [0.60, 1.00]
>>> sum(choices('HT', cum_weights=cw, k=7).count('H') >= 5 for i in range(n)) / n
0.4169
Example of `statistical bootstrapping
<https://en.wikipedia.org/wiki/Bootstrapping_(statistics)>`_ using resampling
with replacement to estimate a confidence interval for the mean of a small