mann-whitney test

C2
UK/ˌmæn ˈwɪtni ˌtɛst/US/ˌmæn ˈ(h)wɪtni ˌtɛst/

Technical/Formal

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Definition

Meaning

A non-parametric statistical test used to compare the distributions of two independent groups when the dependent variable is ordinal or continuous but not normally distributed.

A rank-based statistical hypothesis test that assesses whether two independent samples are likely to derive from the same population distribution. It is often used as an alternative to the independent samples t-test when its assumptions are violated. The null hypothesis is that the probability of a randomly selected value from one group being greater than a value from the other is 0.5.

Linguistics

Semantic Notes

This term is a proper noun (derived from the surnames of its developers, Frank Wilcoxon, Henry Mann, and Donald Whitney) and is almost exclusively used in technical, academic, or research contexts. It is sometimes called the 'Mann-Whitney U test' or 'Wilcoxon rank-sum test.'

Dialectal Variation

British vs American Usage

Differences

There is no significant difference in meaning or spelling. British academic writing may be slightly more likely to reference the 'Wilcoxon rank-sum test' or simply 'Wilcoxon test' in some disciplines, while American writing may use 'Mann-Whitney U test' more consistently, but both terms are fully understood and used interchangeably in both regions.

Connotations

None beyond its precise statistical meaning.

Frequency

The term is extremely rare outside of statistics, research methods, psychology, medicine, and other empirical sciences. Its frequency is identical in UK and US academic English.

Vocabulary

Collocations

strong
perform a Mann-Whitney testrun a Mann-Whitney testMann-Whitney test was usedMann-Whitney test resultsMann-Whitney U statistic
medium
apply the Mann-Whitney testsignificant in the Mann-Whitney testnon-significant Mann-Whitney testfollowing a Mann-Whitney test
weak
parametric Mann-Whitney testsimple Mann-Whitney testMann-Whitney test analysis

Grammar

Valency Patterns

The researchers performed a [Mann-Whitney test] on the two groups.A [Mann-Whitney test] revealed a significant difference.The data were analysed using [the Mann-Whitney test].

Vocabulary

Synonyms

Strong

Wilcoxon-Mann-Whitney test

Neutral

Mann-Whitney U testWilcoxon rank-sum test

Weak

non-parametric t-test alternativerank-based comparison test

Vocabulary

Antonyms

independent samples t-testparametric testpaired samples test

Phrases

Idioms & Phrases

  • It's not a t-test, it's a Mann-Whitney.

Usage

Context Usage

Business

Virtually never used, except in highly specialised business analytics or data science roles.

Academic

Primary context. Common in research papers, theses, and methodology sections of empirical studies in social sciences, medicine, and biology.

Everyday

Never used.

Technical

Core context. Standard terminology in statistics, data analysis software (e.g., SPSS, R), and research methodology.

Examples

By Part of Speech

verb

British English

  • The data were Mann-Whitney tested due to non-normal distributions.

American English

  • We need to Mann-Whitney these two sets of scores.

adjective

British English

  • The Mann-Whitney analysis yielded a significant p-value.

American English

  • The Mann-Whitney result indicated a group difference.

Examples

By CEFR Level

A2
  • This sentence is not applicable for A2 level.
B1
  • Scientists sometimes use a special test called the Mann-Whitney test when their data is not normal.
B2
  • Because the satisfaction scores were ordinal and not normally distributed, the researcher chose to analyse them with a Mann-Whitney test.
C1
  • A Mann-Whitney U test was conducted to determine if there was a difference in reaction times between the control and experimental groups, as the Shapiro-Wilk test indicated a violation of normality (W = 0.87, p < .05).

Learning

Memory Aids

Mnemonic

Remember 'MANN' as in 'Manual' ranking and 'WHITNEY' as in 'Which one is higher?' – it's a test to see which of two independent groups tends to have higher ranked scores.

Conceptual Metaphor

A RANKING CONTEST. The test metaphorically lines up all scores from both groups in one long race, gives each a rank (1st, 2nd, 3rd...), and then checks if one team's runners consistently finished ahead of the other's.

Watch out

Common Pitfalls

Translation Traps (for Russian speakers)

  • Do not translate the surnames ('Mann' is not 'мужчина', 'Whitney' is not 'белый').
  • Avoid literal translation like 'тест мужчины-Уитни'. Use the established loan term 'U-критерий Манна-Уитни' or 'критерий Манна-Уитни'.
  • Do not confuse with the 'Wilcoxon signed-rank test' (критерий Уилкоксона для связанных выборов), which is for paired samples.

Common Mistakes

  • Using it for paired or dependent samples (the Wilcoxon signed-rank test is correct for that).
  • Referring to it as 'the Mann test' or 'the Whitney test'.
  • Misspelling as 'Man-Whitney test', 'Mann-Whitny test', or 'Mann-Whitney's test'.
  • Using it when data are normally distributed and an independent t-test would be more powerful.

Practice

Quiz

Fill in the gap
When the assumption of normality is violated for a between-subjects design, researchers often employ the as a non-parametric alternative.
Multiple Choice

The Mann-Whitney test is most appropriately used under which of the following conditions?

FAQ

Frequently Asked Questions

The independent samples t-test compares means and assumes normally distributed data and homogeneity of variances. The Mann-Whitney test compares distributions (often interpreted as comparing medians) and makes no assumption of normality, making it a non-parametric, rank-based test.

No. For paired or matched data (e.g., pre-test/post-test scores from the same individuals), the appropriate non-parametric alternative is the Wilcoxon signed-rank test.

The 'U' stands for the test statistic calculated during the procedure. It represents the number of times a score from one group precedes a score from the other group in the combined ranking. A small U value indicates a large difference between the groups.

No, best practice includes reporting the U statistic, the sample sizes (n1, n2), the exact p-value, and an effect size measure (commonly r = Z/√N) to convey the magnitude of the observed difference, not just its statistical significance.