bootstrapping: comparing sample means

.gitignore

sample_a.dat
sample_b.dat

README.md

Students should extract subsets of data from particular groups within their data set for this exercise. In the absense of that, you can run the create_sample.py script to create the sample and then run the compare_sample_means.py script to compare the two groups.

compare_sample_means.py

#!/usr/bin/env python

"""Given two files that contain a list of data values, compute the
differences in the sample means with a bootstrapping approach
"""

import random

def read_data(filename):
    with open(filename) as stream:
        return map(float, stream.read().split())

def calculate_sample_mean(n, data):
    sample = [random.choice(data) for i in xrange(n)]
    return sum(sample) / n

m = 1000
n = 100

a_data = read_data('sample_a.dat')
b_data = read_data('sample_b.dat')


# calculate a bunch of sample means
count = 0
for j in xrange(m):
    a_mean = calculate_sample_mean(n, a_data)
    b_mean = calculate_sample_mean(n, b_data)
    if a_mean > b_mean:
        count += 1

print("a_mean > b_mean %(count)d out of %(m)d times" % locals())

create_sample.py

#!/usr/bin/env python

"""I don't currently have access to the movie or horse racing data, so
use this script to create the group a and group b data sets that are
used in subsequent steps.
"""

import sys
import random

def write_sample(stream, n, lam):
    filename = stream.name
    sys.stderr.write((
        '%(filename)s with %(n)d values from exponential distribution'
        'with lam=%(lam)s\n'
    ) % locals())
    for i in xrange(n):
        x = random.expovariate(lam)
        stream.write(str(x) + '\n')

with open('sample_a.dat', 'w') as stream:
    write_sample(stream, 100000, 1.5)

with open('sample_b.dat', 'w') as stream:
    write_sample(stream, 20000, 1.1)