title: AttributeError: 'OLSResults' object has no attribute 'norm_resid'
body: <p>When I run this I have the following error : </p>
  
  <pre class="lang-none prettyprint-override"><code>AttributeError: 'OLSResults' object has no attribute 'norm_resid'
  </code></pre>
  
  <p>I have the latest version of OLS, so the attribute <code>norm_resid</code> should be there. </p>
  
  <p>Any ideas ?</p>
  
  <pre><code>from scipy import stats
  from pandas import Series, DataFrame
  import pandas as pd
  import numpy as np
  import matplotlib.pylab as plt
  from sklearn import datasets, linear_model
  from statsmodels.formula.api import ols
  """
  Data Management
  """
  data = pd.read_csv("TestExer1-sales-round1.csv")
  X_train = data["Advertising"]
  Y_train  = data["Sales"]
  
  
  # use of linregregress
  model = ols("Y_train ~ X_train", data).fit()
  print(model.summary()) 
  
  plt.plot(X_train,Y_train , 'ro')
  plt.plot(X_train, model.fittedvalues, 'b')
  plt.legend(['Sales', 'Advertising'])
  plt.ylim(0, 70)
  plt.xlim(5, 18)
  plt.hist(model.norm_resid())
  plt.ylabel('Count')
  plt.xlabel('Normalized residuals')
  
  plt.xlabel('Temperature')
  plt.ylabel('Gas')
  plt.title('Before Insulation')
  </code></pre>