Beispiel #1
0
        pyplot.plot(weeks, v, label=k)

    myplot.Save(root='2_7',
                xlabel='weeks',
                ylabel=r'Prob{x $=$ weeks | x $\geq$ weeks}',
                title='Conditional Probability')


# On first blush, this is really just another survival analysis problem. So
# we build a Pmf.Pmf for babies' births and use the same kind of analysis
# as we did for Exercise 2-4 using utils.remaining_lifetime.
if __name__ == '__main__':
    data_dir = sys.argv[1]
    table = survey.Pregnancies()
    table.ReadRecords(data_dir)
    firsts, others = partition_births(table)

    descriptive.Process(firsts, 'firsts')
    descriptive.Process(others, 'others')

    # Part 1 - conditional probability that a baby will be born in week 39
    # Relevant output from official code:
    # 39 0.633693045564 first babies
    # 39 0.715792395226 others
    _print_survival_analysis(39, firsts)
    _print_survival_analysis(39, others)

    # Part 2 isn't really a meaningful task if we're right to just use
    # the survival analysis approach. In that case, Part 1 was just a
    # special use case. Let's demonstrate this.
Beispiel #2
0
def prob_in_weeks(pmf, start, end):
    prob_sum = 0
    for val, prob in pmf.Items():
        if start <= val <= end:
            prob_sum += prob
    return prob_sum

prob_early = functools.partial(prob_in_weeks, start=0, end=37)
prob_on_time = functools.partial(prob_in_weeks, start=38, end=40)
prob_late = functools.partial(prob_in_weeks, start=41, end=1000000)

if __name__ == '__main__':
    data_dir = sys.argv[1]
    table = survey.Pregnancies()
    table.ReadRecords(data_dir)
    first_births, other_births = my_first.partition_births(table)

    live_pmf = Pmf.MakePmfFromList([prg.prglength for prg in table.records])
    first_pmf = Pmf.MakePmfFromList([prg.prglength for prg in first_births.records])
    other_pmf = Pmf.MakePmfFromList([prg.prglength for prg in other_births.records])

    prob_early_first = prob_early(first_pmf)
    prob_early_other = prob_early(other_pmf)

    print 'Early probability (all live):', prob_early(live_pmf) * 100
    print 'Early probability (firsts):', prob_early_first * 100
    print 'Early probability (others):', prob_early_other * 100
    print 'Relative risk of being early (first vs. other):', prob_early_first / prob_early_other
    print

    prob_on_time_first = prob_on_time(first_pmf)
Beispiel #3
0
See README.md for more info.
"""
import sys

from my_first import partition_births
import survey
from thinkstats import Mean, Var
from utils import std_dev


if __name__ == '__main__':
    data_dir = sys.argv[1]
    table = survey.Pregnancies()
    table.ReadRecords(data_dir)

    firsts, others = partition_births(table)

    firsts_gestation_lengths = list((p.prglength for p in firsts.records))
    others_gestation_lengths = list((p.prglength for p in others.records))

    for births in (firsts, others):
        births_gestation_lengths = list((p.prglength for p in births.records))
        births.mean = Mean(births_gestation_lengths)
        births.variance = Var(births_gestation_lengths, births.mean)
        births.std_dev = std_dev(births_gestation_lengths, births.mean, births.variance)


    print 'The mean gestation time for firstborns is:', firsts.mean
    print 'The mean gestation time for others is:', others.mean

    print 'The gestation time variance for firstborns is:', firsts.variance
Beispiel #4
0
    prob_sum = 0
    for val, prob in pmf.Items():
        if start <= val <= end:
            prob_sum += prob
    return prob_sum


prob_early = functools.partial(prob_in_weeks, start=0, end=37)
prob_on_time = functools.partial(prob_in_weeks, start=38, end=40)
prob_late = functools.partial(prob_in_weeks, start=41, end=1000000)

if __name__ == '__main__':
    data_dir = sys.argv[1]
    table = survey.Pregnancies()
    table.ReadRecords(data_dir)
    first_births, other_births = my_first.partition_births(table)

    live_pmf = Pmf.MakePmfFromList([prg.prglength for prg in table.records])
    first_pmf = Pmf.MakePmfFromList(
        [prg.prglength for prg in first_births.records])
    other_pmf = Pmf.MakePmfFromList(
        [prg.prglength for prg in other_births.records])

    prob_early_first = prob_early(first_pmf)
    prob_early_other = prob_early(other_pmf)

    print 'Early probability (all live):', prob_early(live_pmf) * 100
    print 'Early probability (firsts):', prob_early_first * 100
    print 'Early probability (others):', prob_early_other * 100
    print 'Relative risk of being early (first vs. other):', prob_early_first / prob_early_other
    print