import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy as sp
import scipy.stats
import sys
weight = pd.read_csv('Davis.csv')['weight'].values
m = weight.mean()
s2 = ((weight - m) ** 2).mean()
a = (weight - m) ** 2 / s2
th = sp.stats.chi2.ppf(0.99, 1)
plt.scatter(np.arange(weight.size), a, color='g')
plt.plot([0, 200], [th, th], color='b', linestyle='-', linewidth=2)
plt.show()

ab46df5e1563e1e338234abd549c451c2b08e29a
<mask token>

<mask token>
plt.scatter(np.arange(weight.size), a, color='g')
plt.plot([0, 200], [th, th], color='b', linestyle='-', linewidth=2)
plt.show()

<mask token>
weight = pd.read_csv('Davis.csv')['weight'].values
m = weight.mean()
s2 = ((weight - m) ** 2).mean()
a = (weight - m) ** 2 / s2
th = sp.stats.chi2.ppf(0.99, 1)
plt.scatter(np.arange(weight.size), a, color='g')
plt.plot([0, 200], [th, th], color='b', linestyle='-', linewidth=2)
plt.show()

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy as sp
import scipy.stats
import sys
weight = pd.read_csv('Davis.csv')['weight'].values
m = weight.mean()
s2 = ((weight - m) ** 2).mean()
a = (weight - m) ** 2 / s2
th = sp.stats.chi2.ppf(0.99, 1)
plt.scatter(np.arange(weight.size), a, color='g')
plt.plot([0, 200], [th, th], color='b', linestyle='-', linewidth=2)
plt.show()
