estimator, unbiased concept
| Definition | A rule that produces an estimate of an unknown quantity from a sample, unbiased when its expectation over samples is that quantity. An estimate without a statement of its spread is not interpretable. Primer S section S.6. Also estimator, unbiased. |
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| Example | The sample variance with n minus 1 is unbiased for the true variance, and with n it is too small by the factor (n minus 1) over n. |
| Book | Data Mining as Observation, draft 0.2, commit f3914f0; entry id estimator, 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.6 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
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Used in
Data Mining as Observation primer S, chapters 1, 2.
Related
sample variance; confidence interval; standard error; bootstrap.
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.