def MakeNormalPlot(weights):
"""Generates a normal probability plot of birth weights.
weights: sequence
"""
mean, var = thinkbayes2.TrimmedMeanVar(weights, p=0.01)
std = math.sqrt(var)
xs = [-5, 5]
xs, ys = thinkbayes2.FitLine(xs, mean, std)
thinkplot.plot(xs, ys, color='0.8', label='model')
xs, ys = thinkbayes2.NormalProbability(weights)
thinkplot.plot(xs, ys, label='weights')
def MakeNormalModel(weights):
"""Plots a CDF with a Normal model.
weights: sequence
"""
cdf = thinkbayes2.Cdf(weights, label='weights')
mean, var = thinkbayes2.TrimmedMeanVar(weights)
std = math.sqrt(var)
print('n, mean, std', len(weights), mean, std)
xmin = mean - 4 * std
xmax = mean + 4 * std
xs, ps = thinkbayes2.RenderNormalCdf(mean, std, xmin, xmax)
thinkplot.plot(xs, ps, label='model', linewidth=4, color='0.8')
thinkplot.cdf(cdf)