title: Converting Numpy Lstsq residual value to R^2
body: <p>I am performing a least squares regression as below (univariate). I would like to express the significance of the result in terms of R^2. Numpy returns a value of unscaled residual, what would be a sensible way of normalizing this.</p>
  
  <pre><code>field_clean,back_clean = rid_zeros(backscatter,field_data)
  num_vals = len(field_clean)
  x = field_clean[:,row:row+1]
  y = 10*log10(back_clean)
  
  A = hstack([x, ones((num_vals,1))])
  soln = lstsq(A, y )
  m, c =  soln [0]
  residues = soln [1]
  
  print residues
  </code></pre>