Kruskal–Wallis test
E387065
The Kruskal–Wallis test is a nonparametric statistical method used to determine whether there are statistically significant differences between the medians of three or more independent groups.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Kruskal–Wallis test canonical | 5 |
| Kruskal–Wallis H test | 1 |
| Kruskal–Wallis one-way analysis of variance by ranks | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3771948 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kruskal–Wallis test Context triple: [Martin David Kruskal, notableWork, Kruskal–Wallis test]
-
A.
Tukey's honestly significant difference test
Tukey's honestly significant difference test is a statistical post-hoc procedure used to determine which specific group means differ after an ANOVA indicates a significant overall effect.
-
B.
Fisher's exact test
Fisher's exact test is a statistical significance test used to determine whether there are nonrandom associations between two categorical variables in a contingency table, especially with small sample sizes.
-
C.
Mauchly
Mauchly is the surname of John W. Mauchly, the American physicist and co-inventor of the ENIAC, one of the earliest general-purpose electronic digital computers.
-
D.
F-test
The F-test is a statistical hypothesis test used to compare variances and assess the overall significance of models, especially in analysis of variance (ANOVA) and regression.
-
E.
Tukey's range test
Tukey's range test is a statistical post-hoc multiple comparison procedure used to determine which group means differ significantly after an ANOVA.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kruskal–Wallis test Target entity description: The Kruskal–Wallis test is a nonparametric statistical method used to determine whether there are statistically significant differences between the medians of three or more independent groups.
-
A.
Tukey's honestly significant difference test
Tukey's honestly significant difference test is a statistical post-hoc procedure used to determine which specific group means differ after an ANOVA indicates a significant overall effect.
-
B.
Fisher's exact test
Fisher's exact test is a statistical significance test used to determine whether there are nonrandom associations between two categorical variables in a contingency table, especially with small sample sizes.
-
C.
Mauchly
Mauchly is the surname of John W. Mauchly, the American physicist and co-inventor of the ENIAC, one of the earliest general-purpose electronic digital computers.
-
D.
F-test
The F-test is a statistical hypothesis test used to compare variances and assess the overall significance of models, especially in analysis of variance (ANOVA) and regression.
-
E.
Tukey's range test
Tukey's range test is a statistical post-hoc multiple comparison procedure used to determine which group means differ significantly after an ANOVA.
- F. None of above. chosen
Statements (50)
| Predicate | Object |
|---|---|
| instanceOf |
hypothesis test
ⓘ
nonparametric statistical test ⓘ omnibus test ⓘ rank-based statistical test ⓘ |
| alsoKnownAs |
Kruskal–Wallis test
ⓘ
surface form:
Kruskal–Wallis H test
one-way ANOVA on ranks ⓘ |
| alternativeHypothesis |
at least one group distribution differs
ⓘ
at least one group median differs ⓘ |
| alternativeTo | one-way ANOVA ⓘ |
| assumes |
independent observations within groups
ⓘ
independent samples ⓘ ordinal or higher level of measurement ⓘ similar shape of distributions across groups ⓘ |
| basedOn | ranks of observations ⓘ |
| canBeUsedWith | two groups ⓘ |
| degreesOfFreedom | k - 1 ⓘ |
| doesNotAssume |
homogeneity of variances as strictly as ANOVA
ⓘ
normal distribution of data ⓘ |
| field |
nonparametric statistics
ⓘ
statistics ⓘ |
| inputType |
continuous data
ⓘ
ordinal data ⓘ |
| namedAfter |
W. Allen Wallis
ⓘ
William Kruskal ⓘ
surface form:
William H. Kruskal
|
| parameterMeaning | number of groups ⓘ |
| parameterSymbol | k ⓘ |
| postHocRequirement | requires multiple comparison procedures to identify which groups differ ⓘ |
| publishedIn | Journal of the American Statistical Association ⓘ |
| purpose | to test for differences between groups ⓘ |
| relatedTo | one-way ANOVA ⓘ |
| requires |
at least five observations per group for chi-square approximation to be accurate
ⓘ
three or more groups ⓘ |
| softwareSupport |
Python statistical libraries
ⓘ
R ⓘ SAS ⓘ IBM SPSS Statistics ⓘ
surface form:
SPSS
Stata ⓘ |
| testsFor | differences in central tendency between groups ⓘ |
| testStatistic | H statistic ⓘ |
| testStatisticDistribution | approximately chi-square distribution under the null hypothesis ⓘ |
| typicalNullHypothesis |
all group distributions are identical
ⓘ
all group medians are equal ⓘ |
| usedIn |
biostatistics
ⓘ
ecology ⓘ psychology ⓘ social sciences ⓘ |
| usedWhen |
ANOVA assumptions are violated
ⓘ
data are ordinal ⓘ data contain outliers ⓘ |
| yearProposed | 1952 ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Kruskal–Wallis test Description of subject: The Kruskal–Wallis test is a nonparametric statistical method used to determine whether there are statistically significant differences between the medians of three or more independent groups.
Referenced by (7)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
John B. Kruskal
subject surface form:
John B. Kruskal
this entity surface form:
Kruskal–Wallis one-way analysis of variance by ranks
this entity surface form:
Kruskal–Wallis H test