title: Calculating confidence intervals for a non-normal distribution
body: <p>First, I should specify that my knowledge of statistics is fairly limited, so please forgive me if my question seems trivial or perhaps doesn't even make sense.</p>
  
  <p>I have data that doesn't appear to be normally distributed.  Typically, when I plot confidence intervals, I would use the mean +- 2 standard deviations, but I don't think that is acceptible for a non-uniform distribution.  My sample size is currently set to 1000 samples, which would seem like enough to determine if it was a normal distribution or not.</p>
  
  <p>I use Matlab for all my processing, so are there any functions in Matlab that would make it easy to calculate the confidence intervals (say 95%)?</p>
  
  <p>I know there are the 'quantile' and 'prctile' functions, but I'm not sure if that's what I need to use.  The function 'mle' also returns confidence intervals for normally distributed data, although you can also supply your own pdf.</p>
  
  <p>Could I use ksdensity to create a pdf for my data, then feed that pdf into the mle function to give me confidence intervals?</p>
  
  <p>Also, how would I go about determining if my data is normally distributed.  I mean I can currently tell just by looking at the histogram or pdf from ksdensity, but is there a way to quantitatively measure it?</p>
  
  <p>Thanks!</p>