Tukey's honestly significant difference test
E371261
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.
All labels observed (6)
How this entity was disambiguated
This entity first appeared as the object of triple T3600026 — 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: Tukey's honestly significant difference test Context triple: [John W. Tukey, developedConcept, Tukey's honestly significant difference test]
-
A.
Hotelling’s T-squared distribution
Hotelling’s T-squared distribution is a multivariate generalization of Student’s t-distribution used primarily for hypothesis testing and constructing confidence regions for mean vectors in multivariate statistics.
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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.
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C.
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.
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D.
Neyman–Pearson theory of hypothesis testing
The Neyman–Pearson theory of hypothesis testing is a foundational statistical framework that formalizes how to construct and evaluate tests for competing hypotheses using concepts like Type I and Type II errors and power.
-
E.
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.
- 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: Tukey's honestly significant difference test Target entity description: 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.
-
A.
Hotelling’s T-squared distribution
Hotelling’s T-squared distribution is a multivariate generalization of Student’s t-distribution used primarily for hypothesis testing and constructing confidence regions for mean vectors in multivariate statistics.
-
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.
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.
-
D.
Neyman–Pearson theory of hypothesis testing
The Neyman–Pearson theory of hypothesis testing is a foundational statistical framework that formalizes how to construct and evaluate tests for competing hypotheses using concepts like Type I and Type II errors and power.
-
E.
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.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
multiple comparison procedure
ⓘ
pairwise comparison method ⓘ post-hoc test ⓘ statistical test ⓘ |
| alsoKnownAs |
Tukey's HSD test
ⓘ
Tukey's honestly significant difference test ⓘ
surface form:
Tukey's honestly significant difference procedure
Tukey's range test ⓘ |
| appliesTo | all pairwise comparisons of group means ⓘ |
| assumes |
homogeneity of variances
ⓘ
independent observations ⓘ normally distributed errors ⓘ |
| basedOn | studentized range distribution ⓘ |
| canBeUsedWith | unequal sample sizes with approximations ⓘ |
| category | parametric test ⓘ |
| commonlyUsedIn |
agricultural experiments
ⓘ
biomedical research ⓘ experimental design analysis ⓘ psychology research ⓘ |
| compares | absolute differences between group means ⓘ |
| controls | family-wise error rate ⓘ |
| decisionRule | declare difference significant if mean difference exceeds HSD critical value ⓘ |
| developedBy |
John W. Tukey
ⓘ
surface form:
John Tukey
|
| field | statistics ⓘ |
| implementedIn |
Python statistical libraries
ⓘ
R ⓘ SAS ⓘ IBM SPSS Statistics ⓘ
surface form:
SPSS
Stata ⓘ |
| input |
group means
ⓘ
mean square error from ANOVA ⓘ sample sizes per group ⓘ |
| lessConservativeThan | Scheffé's method ⓘ |
| moreConservativeThan | Fisher's LSD test ⓘ |
| output |
critical difference between means
ⓘ
significance decisions for each pair of means ⓘ |
| purpose |
to control family-wise error rate in multiple comparisons
ⓘ
to determine which specific group means differ ⓘ |
| relatedTo |
Bonferroni correction
ⓘ
Dunnett's test ⓘ Fisher's LSD test ⓘ Scheffé's method ⓘ |
| requires |
equal sample sizes for exact critical values
ⓘ
pre-specified significance level alpha ⓘ significant overall ANOVA F-test before application ⓘ |
| subfield |
analysis of variance methods
ⓘ
inferential statistics ⓘ |
| usedAfter |
analysis of variance
ⓘ
one-way ANOVA ⓘ |
| usesStatistic | studentized range statistic q ⓘ |
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: Tukey's honestly significant difference test Description of subject: 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.
Referenced by (9)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
John W. Tukey
this entity surface form:
Tukey test
subject surface form:
John W. Tukey
this entity surface form:
Tukey’s honestly significant difference test
this entity surface form:
Tukey's HSD test
this entity surface form:
Tukey's Honestly Significant Difference test
this entity surface form:
Tukey's honestly significant difference procedure
Tukey's honestly significant difference test
→
alsoKnownAs
→
Tukey's honestly significant difference test
ⓘ
this entity surface form:
Tukey's honestly significant difference procedure
subject surface form:
John W. Tukey
this entity surface form:
Tukey test