First I'll start out with some background information. I conducted image analysis on 200 images to identify the area % of 7 different phases. I then averaged the results from each of for the 200 images to determine the average area % for each phase. For example phase 1 the average area is 20.1%.
Typically, I would like to report average results from a test with the mean +- 1.96 x SE, if it is normally distributed. Therefore, I conducted Anderson Darling tests on the area % data to determine if the data followed a normal, exponential, weibull, or gamma distribution, or could be transformed into one of those. However, all aforementioned distributions failed the Anderson Darling test with p-values that exceed 0.10.
Am I likely failing the distribution identification tests, because my average area % is a discrete variable and is not continuous (aka it only ranges from 0 to 100%)?