Quantile-Quantile comparisons are used often to test normality of experimental data in q-q plots. This method can be extended to compare sampling distributions and to test whether they are similarly distributed. AFIS distribution data seems to be important in determining spinning characteristics of cotton varieties, but using the distribution in an experimental setting is more complicated than testing means, C.V.s or variances. Comparisons of "ideal" fiber distributions, experimental checks, and theoretical distributions as controls for testing will be discussed. Complications for comparing distributions across replications and locations will be discussed as well as comparisons to other testing methods such as cross-entropy.