title: `ValueError: too many values to unpack (expected 4)` with `scipy.stats.linregress`
body: <p>I know that this error message (<code>ValueError: too many values to unpack (expected 4)</code>) appears when more variables are set to values than a function returns. </p>
  
  <p><code>scipy.stats.linregress</code> returns 5 values according to the scipy documentation (<a href="http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.linregress.html" rel="noreferrer">http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.linregress.html</a>).</p>
  
  <p>Here is a short, reproducible example of a working call, and then a failed call, to <code>linregress</code>:</p>
  
  <p>What could account for difference and why is the second one poorly called?</p>
  
  <pre><code>from scipy import stats
  import numpy as np
  
  if __name__ == '__main__':
      x = np.random.random(10)
      y = np.random.random(10)
      print(x,y)
      slope, intercept, r_value, p_value, std_err = stats.linregress(x,y)
  
  
  '''
  Code above works
  Code below fails
  '''
  
      X = np.asarray([[-15.93675813],
   [-29.15297922],
   [ 36.18954863],
   [ 37.49218733],
   [-48.05882945],
   [ -8.94145794],
   [ 15.30779289],
   [-34.70626581],
   [  1.38915437],
   [-44.38375985],
   [  7.01350208],
   [ 22.76274892]])
  
      Y = np.asarray( [[  2.13431051],
   [  1.17325668],
   [ 34.35910918],
   [ 36.83795516],
   [  2.80896507],
   [  2.12107248],
   [ 14.71026831],
   [  2.61418439],
   [  3.74017167],
   [  3.73169131],
   [  7.62765885],
   [ 22.7524283 ]])
  
      print(X,Y) # The array initialization succeeds, if both arrays are print out
  
  
      for i in range(1,len(X)):
          slope, intercept, r_value, p_value, std_err = (stats.linregress(X[0:i,:], y = Y[0:i,:]))
  </code></pre>