independence concept
| Definition | Two events are independent when knowing one changes nothing about the other, so that the probability of both is the product. Independent variables have variances that add, and tests on overlapping data are not independent. Primer S, equation S.2. |
|---|---|
| Example | The first die showing three and the sum being seven have joint probability 1/36, the product of 1/6 and 1/6, so they are independent. |
| Book | Data Mining as Observation, draft 0.2, commit f3914f0; entry id independence, kind concept. |
| Status | no ledger row names this entry. Corrections: none recorded. |
| Defining equation | Book equation S.2. |
| 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
Book equation S.2.
\[\Pr[A\mid B]=\frac{\Pr[A\cap B]}{\Pr[B]},\qquad A,B\ \text{independent}\iff \Pr[A\cap B]=\Pr[A]\,\Pr[B].\]
Conditions
none
Ledger
none
First stated
Primer S section S.1 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 primers L and S, chapters 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14.
Related
conditional probability; variance; multiple comparisons.
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.