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permutation test concept

DefinitionA test that computes the p-value by reassigning the labels under the null, every way or a few thousand random ways, and counting the fraction of statistics at least as extreme as the observed. It needs no assumption about the shape of the data, and the sample size fixes the smallest p-value it can give. Primer S, equation S.15. Also permut.
ExampleGroups (8, 9) and (4, 5) have six reassignments, two with a difference of at least 4 in size, so the two-sided p-value is one third.
BookData Mining as Observation, draft 0.2, commit f3914f0; entry id permutation-test, kind concept.
Statusno ledger row names this entry. Corrections: none recorded.
Defining equation

Book equation S.15.

Assumptions and scopenone
Prior artnone recorded
Evidencenone
Reviewedsemantic review 2026-09-09; generated 2026-09-10 from records at the commits on the provenance page.

Equation

Book equation S.15.

\[p=\Pr\big[\,|T|\ge|t_{\mathrm{obs}}|\ \big|\ \text{null}\,\big]=\frac{\#\{\text{reassignments with } |T|\ge|t_{\mathrm{obs}}|\}}{\#\{\text{reassignments}\}}.\]

Conditions

none

Ledger

none

First stated

Primer S section S.7 of Data Mining as Observation, added in draft 0.3 (2026-09-09) for the ECE 514 readers whose first courses are far behind. The idea is standard and TSK Appendix C covers it at length.

Measurements

none

Failures and corrections

none

Invariance envelope

none declared

Machine checked

none

Used in

Data Mining as Observation primer S, chapters 0, 7, 8, 9, 14.

Related

null hypothesis; p-value; null model; seed; type I and type II error, power.

See also

none

Status

Generated 2026-09-10 by encyclopedia/generate.py; book at observation-data-mining f3914f0; the commit of every record is listed in the encyclopedia’s provenance.

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