title: fitting beta distribution (in python) - clarification please
body: <p>I am fitting a beta distribution with beta.fit(W). The values of W do not reach the [0,1] boundaries. My question is the following - do I need to force [0,1] bounds by beta.fit(W,loc = min(W),scale = max(W) - min(W)), or may I assume that as long as the data is within the [0,1] range, the fitting "will be fine"? Obviously, scaling the data should give different values of a and b. Which one is the "correct one"? </p>
  
  <p>This question is related to:
  <a href="https://stats.stackexchange.com/questions/68983/beta-distribution-fitting-in-scipy">https://stats.stackexchange.com/questions/68983/beta-distribution-fitting-in-scipy</a></p>
  
  <p>Unfortunately, no valid answer on what to do when the data is within the expected range is give... </p>
  
  <p>I tried to fit data generated with known values of a and b and neither technique gave a good fit, although scaling seemed to help a bit. </p>
  
  <p>Thanks</p>