Editing Mann–Whitney U test (section)

==Software implementations==
In many software packages, the Mann–Whitney ''U'' test (of the hypothesis of equal distributions against appropriate alternatives) has been poorly documented. Some packages incorrectly treat ties or fail to document asymptotic techniques (e.g., correction for continuity). A 2000 review discussed some of the following packages:<ref>{{cite journal |title=Different Outcomes of the Wilcoxon–Mann–Whitney Test from Different Statistics Packages |first1=Reinhard |last1=Bergmann |first2=John |last2=Ludbrook |first3=Will P.J.M. |last3=Spooren |journal=The American Statistician |volume=54 |issue=1 |year=2000 |pages=72–77 |jstor=2685616 |doi=10.1080/00031305.2000.10474513|s2cid=120473946 }}</ref>

* [[MATLAB]] has [http://www.mathworks.co.uk/help/stats/ranksum.html {{mono|ranksum}}] in its Statistics Toolbox.
* [[R (programming language)|R]]'s statistics base-package implements the test [http://stat.ethz.ch/R-manual/R-patched/library/stats/html/wilcox.test.html {{mono|wilcox.test}}] in its "stats" package.
* The R function [https://search.r-project.org/CRAN/refmans/rcompanion/html/wilcoxonZ.html {{mono|wilcoxonZ}}] from the [https://CRAN.R-project.org/package=rcompanion {{mono|rcompanion}}] package will calculate the {{Math|''z''}} statistic for a Wilcoxon two-sample, paired, or one-sample test.
* [[SAS (software)|SAS]] implements the test in its <code>PROC NPAR1WAY</code> procedure.
* [[Python (programming language)|Python]] has an implementation of this test provided by [[SciPy]].<ref>{{cite web |url=http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.mannwhitneyu.html |title=scipy.stats.mannwhitneyu |work=SciPy v0.16.0 Reference Guide |author=<!--Staff writer(s); no by-line.--> |date=24 July 2015 |publisher=The Scipy community |access-date=11 September 2015 |quote=scipy.stats.mannwhitneyu(x, y, use_continuity=True): Computes the Mann–Whitney rank test on samples&nbsp;x and&nbsp;y.}}</ref>
* [[SigmaStat]] (SPSS Inc., Chicago, IL)
* [[SYSTAT (statistics)|SYSTAT]] (SPSS Inc., Chicago, IL)
* [[Java (programming language)|Java]] has an implementation of this test provided by [[Apache Commons]]<ref>{{Cite web|url=http://commons.apache.org/proper/commons-math/javadocs/api-3.3/org/apache/commons/math3/stat/inference/MannWhitneyUTest.html|title=MannWhitneyUTest (Apache Commons Math 3.3 API)|website=commons.apache.org}}</ref>
*[[Julia (programming language)|Julia]] has implementations of this test through several packages.  In the package <code>HypothesisTests.jl</code>, this is found as <code>pvalue(MannWhitneyUTest(X, Y))</code>.<ref>{{Cite web|url=https://github.com/JuliaStats/HypothesisTests.jl|title=JuliaStats/HypothesisTests.jl|website=GitHub|date=30 May 2021}}</ref>
* [[JMP (statistical software)|JMP]] (SAS Institute Inc., Cary, NC)
* [[S-Plus]] (MathSoft, Inc., Seattle, WA)
* [[STATISTICA]] (StatSoft, Inc., Tulsa, OK)
* [[UNISTAT]] (Unistat Ltd, London)
* [[SPSS]] (SPSS Inc, Chicago)
* [[StatsDirect]] (StatsDirect Ltd, Manchester, UK) implements [http://www.statsdirect.com/help/Default.htm#nonparametric_methods/mann_whitney.htm all common variants].
* [[Stata]] (Stata Corporation, College Station, TX) implements the test in its [https://www.stata.com/help.cgi?ranksum {{mono|ranksum}}] command.
* [[StatXact]] (Cytel Software Corporation, Cambridge, Massachusetts)
* [[PSPP]] implements the test in its [https://www.gnu.org/software/pspp/manual/html_node/WILCOXON.html {{mono|WILCOXON}}] function.
* [[KNIME]] implements the test in its [https://hub.knime.com/knime/extensions/org.knime.features.stats2/latest/org.knime.base.node.stats.testing.wilcoxonmannwhitney.WilcoxonMannWhitneyNodeFactory Wilcoxon–Mann–Whitney Test] node.