When goodness-of-fit values are displayed, as in the distribution fitting comparison chart, p-values are displayed for some combinations of ranking methods and fitted distributions. These express the degree to which the actual fit conforms to a theoretical fit for that fitting test and distribution (see Goodness Of Fit for more information). When the Chi-square method is used, p-values are displayed for all continuous and discrete distributions. P-values are also displayed for the following continuous distributions when the Anderson-Darling or Kolmogorov-Smirnov methods are used: normal, exponential, logistic, maximum extreme, minimum extreme, uniform, gamma, Weibull, and lognormal. P-values for the other distributions are under development.
Since p-values for Anderson-Darling and Kolmogorov-Smirnov statistics are influenced by the number of data points being fitted, an adjustment formula is used to arrive at the asymptotic Anderson-Darling and Kolmogorov-Smirnov statistic for a given sample size. The quality of fitted parameters and the calculated p-value deteriorates as the sample size decreases. Currently, Crystal Ball needs at least 15 data points for fitting all the distributions.