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\textbf{\label{fig:ipython}} Working with the Normal Distribution in iPython\\  Source: \url{http://www.arachnoid.com/IPython/normal_distribution.html}  diff --git a/figures/pdf1/normal_distribution.ipynb b/figures/pdf1/normal_distribution.ipynb  deleted file mode 100644  index 7ad8cd5..0000000  --- a/figures/pdf1/normal_distribution.ipynb  +++ /dev/null 
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import numpy as np  from sympy import *  from IPython.display import *  init_printing  import matplotlib.pyplot as plt  %matplotlib inline  fig = plt.gcf()  fig.set_size_inches(8,5)  var('a b x sigma mu')  pdf = Lambda((x,mu,sigma),  (1/(sigma * sqrt(2*pi)) * exp(-(mu-x)**2 / (2*sigma**2)))  )  x = np.linspace(50,150,100)  y = np.array([pdf(v,100,15) for v in x],dtype='float')  plt.grid(True)  plt.title('Probability Density Function')  plt.xlabel('IQ')  plt.ylabel('Y')  plt.text(122,0.023,'$\mu = 100$',fontsize=16)  plt.text(122,0.021,'$\sigma = 15$',fontsize=16)  plt.plot(x,y,color='gray')  plt.fill_between(x,y,0,color='#c0f0c0')  plt.show()  diff --git a/figures/pdf1/normal_distribution_d3js.html b/figures/pdf1/normal_distribution_d3js.html  deleted file mode 100644  index d6dc959..0000000  --- a/figures/pdf1/normal_distribution_d3js.html  +++ /dev/null 
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        Histogram Sampling a Normal Distribution           

Resample

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height = 700\nwidth = 500