type I and type II error, power concept
| Definition | A type I error rejects a true null, at the rate the threshold fixes. A type II error fails to reject a false null, and power is one minus that rate, growing with the sample size and the size of the effect. Primer S section S.7. Also type I error, type II error, statistical power. |
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| Example | With two values per group the smallest possible p-value is one sixth, so at a threshold of 0.05 the test has no power at all. |
| Book | Data Mining as Observation, draft 0.2, commit f3914f0; entry id type-i-type-ii-error, kind concept. |
| Status | no ledger row names this entry. Corrections: none recorded. |
| Defining equation | none |
| Assumptions and scope | none |
| Prior art | none recorded |
| Evidence | none |
| Reviewed | semantic review 2026-09-09; generated 2026-09-10 from records at the commits on the provenance page. |
Equation
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Conditions
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Ledger
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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
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Failures and corrections
none
Invariance envelope
none declared
Machine checked
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Used in
Data Mining as Observation primer S.
Related
null hypothesis; p-value; multiple comparisons; permutation test.
See also
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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.