I have ~500 of (experimental) samples of data from a range [0,1], and I would like to see if the overall distribution is uniform or whether there is some clustering going on. I would have used Chi-Squared test as recommended here (https://math.stackexchange.com/questions/2435/is-there-a-simple-test-for-uniform-distributions), but there are two problems
- Each sample is small (3-10 datapoints), which is probably too small for a Chi-squared test
- The particular interval in which clustering may occur varies, e.g. for one samples it may be at ~0.2 and for another at ~0.5 etc
- I see some clustering using visualisations, but there is a small number of outliers so I can't rescale each sample based on the value of the first datapoint.
Is there a statistical test / some other approach that I could use?