statistics.mean of bools

[PeterNorvig]

BPO	26913
Nosy	@stevendaprano, @bitdancer
Superseder	bpo-24068: statistics module - incorrect results with boolean input

^{Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.}

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GitHub fields:

assignee = None
closed_at = <Date 2016-05-02.21:41:14.334>
created_at = <Date 2016-05-02.20:59:11.028>
labels = ['type-bug', 'library']
title = 'statistics.mean of bools'
updated_at = <Date 2016-05-02.21:41:14.332>
user = 'https://bugs.python.org/PeterNorvig'

bugs.python.org fields:

activity = <Date 2016-05-02.21:41:14.332>
actor = 'r.david.murray'
assignee = 'none'
closed = True
closed_date = <Date 2016-05-02.21:41:14.334>
closer = 'r.david.murray'
components = ['Library (Lib)']
creation = <Date 2016-05-02.20:59:11.028>
creator = 'Peter.Norvig'
dependencies = []
files = []
hgrepos = []
issue_num = 26913
keywords = []
message_count = 2.0
messages = ['264670', '264675']
nosy_count = 3.0
nosy_names = ['steven.daprano', 'r.david.murray', 'Peter.Norvig']
pr_nums = []
priority = 'normal'
resolution = 'duplicate'
stage = 'resolved'
status = 'closed'
superseder = '24068'
type = 'behavior'
url = 'https://bugs.python.org/issue26913'
versions = ['Python 3.5', 'Python 3.6']

[PeterNorvig]

mean([True, True, True, False]) should be 0.75, but it returns 0.25.

The fix is to change _sum so that when the type is bool, the result should be coerced to int, not bool.

Why it is important for statistics.mean to work with bools:
It is natural to say something like
mean(x > threshold for x in data)
and expect to get the percentage of items in data that are above threshold.

[bitdancer]

Already fixed: bpo-24068.