title: Numpy and matlab polyfit results differences
body: <p>I'm getting different results when calling numpy.polyfit and matlab polyfit functions on exemplary set of data:</p>
  
  <p>Python3.2:</p>
  
  <pre><code>(Pdb) a_array = [1, 2, 4, 6, 8,7, 9]
  (Pdb) numpy.polyfit( range (len (a_array)), a_array, 1)
  array([ 1.35714286,  1.21428571])
  </code></pre>
  
  <p>Matlab:</p>
  
  <pre><code>a_array = [1, 2, 4, 6, 8,7, 9]
  polyfit(1:1:length(a_array), a_array, 1)
  
  ans =
      1.3571   -0.1429
  </code></pre>
  
  <p>This is obviously not a numerical error. </p>
  
  <p>I assume that the default value of some special option (like ddof in std function) differs between Python and matlab but I can't find it. Or maybe I should use another version of Python's polyfit?</p>
  
  <p>How can I get the same polyfit results in both, Python Numpy and Matlab?</p>