def CH7_1():
"""
球队2010-2011赛季, 平均每场进球的分布, 大致为均值2.8, 标准差为0.3的高斯分布
"""
pmf = thinkbayes.MakeGaussianPmf(2.8, 0.3, 4, n=101)
thinkplot.Clf()
thinkplot.Pmf(pmf)
thinkplot.Show();
def __init__(self, exam, score):
self.exam = exam
self.score = score
# start with the Gaussian prior
efficacies = thinkbayes.MakeGaussianPmf(0, 1.5, 3)
thinkbayes.Suite.__init__(self, efficacies)
# update based on an exam score
self.Update(score)
def __init__(self, name=''):
"""Initializes the Hockey object.
name: string
"""
if USE_SUMMARY_DATA:
# prior based on each team's average goals scored
mu = 2.8
sigma = 0.3
else:
# prior based on each pair-wise match-up
mu = 2.8
sigma = 0.85
pmf = thinkbayes.MakeGaussianPmf(mu, sigma, 4)
thinkbayes.Suite.__init__(self, pmf, name=name)
def CalibrateDifficulty(self):
"""Make a plot showing the model distribution of raw scores."""
thinkplot.Clf()
thinkplot.PrePlot(num=2)
cdf = thinkbayes.MakeCdfFromPmf(self.raw, name='data')
thinkplot.Cdf(cdf)
efficacies = thinkbayes.MakeGaussianPmf(0, 1.5, 3)
pmf = self.MakeRawScoreDist(efficacies)
cdf = thinkbayes.MakeCdfFromPmf(pmf, name='model')
thinkplot.Cdf(cdf)
thinkplot.Save(root='sat_calibrate',
xlabel='raw score',
ylabel='CDF',
formats=['pdf', 'eps'])
def __init__(self, mu, sigma, name=''):
"""
"""
pmf = thinkbayes.MakeGaussianPmf(mu, sigma, 1)
thinkbayes.Suite.__init__(self, pmf, name=name)
