Setting Options

Option Name	Description
Plots
By default, plots are included in the results. These plots are determined by the options that you select. Here are some of the plots that you can create: By selecting the options in the Location Differences section, you can create a box plot of Wilcoxon scores, a stacked bar chart showing frequencies above or below the overall median, a box plot of Van der Waerden scores, and a box plot of Savage scores. By selecting the options in the Scale Differences section, you can create a box plot of Ansari-Bradley scores, a box plot of Klotz scores, a box plot of Mood scores, and a box plot of Siegel-Tukey scores. By selecting the options in the Location and Scale Differences section, you can create a box plot of Conover scores. By selecting the Empirical distribution function tests, including Kolmogorov-Smirnov and Cramer-von Mises tests option, you can create a plot of the empirical distribution test. You can specify whether to display the p-values in the plot. To suppress the plots from the results, select the Suppress plots check box.
Tests
Tests	specifies whether to calculate only the asymptotic tests or both the asymptotic tests and exact tests for the various analyses.
Location Differences
Wilcoxon scores	ranks of the observations.
Median scores	equals 1 for observations greater than the median and 0 otherwise.
Van der Waerden scores	the quantiles of a standard normal distribution. These scores are also known as quantile normal scores.
Savage scores	the expected values of order statistics from the exponential distribution with 1 subtracted to center the scores around 0.
Scale Differences
Ansari-Bradley scores	similar to the Siegel-Tukey scores, but assigns the same scores to corresponding extreme ranks.
Klotz scores	the squares of the Van der Waerden (or quantile normal) scores.
Mood scores	the square of the difference between each rank and the average rank.
Siegel-Tukey scores	scores are computed as . The score values continue to increase in this pattern toward the middle ranks until all observations are assigned a score.
Location and Scale Differences
Conover scores	based on the squared ranks of the absolution deviations from the sample means.
Additional Tests
Empirical distribution function tests, including Kolmogorov-Smirnov and Cramer-von Mises tests	the empirical distribution function (EDF) statistics.
Pairwise multiple comparison analysis (asymptotic only)	computes the Dwass, Steel, Critchlow-Fligner (DSCF) multiple comparison analyses.
Details
Continuity Correction
Continuity correction for two sample Wilcoxon and Siegel-Tukey tests	uses a continuity correction for the asymptotic two-sample Wilcoxon and Siegel-Tukey tests by default. The task incorporates this correction when computing the standardized test statistic z by subtracting 0.5 from the numerator if it is greater than zero. If the numerator is less than zero, the task adds 0.5.
Exact Statistics Computation
Use Monte Carlo estimation	requests the Monte Carlo estimation of the exact p-values instead of using the direct exact p-value computation. You can also specify the level of the confidence limits for the Monte Carlo p-value estimates.
Limit computation time	specifies the time limit for calculating each exact p-value. Calculating exact p-values can consume a large amount of time and memory.