How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Conditioning on trivial and full sigma algebras
Example
Under the AC conditional-class convention, for integrable real X, and as classes.
Facts & Assumptions
Given: A probability space and real integrable X; AC is the conditional-class convention.
A known variable conditions to itself, and a variable independent of the conditioning sigma-algebra conditions to its mean. (Conditioning a known variable and an independent variable)
Finite weights summing to one define a probability space. (Finite probability spaces are exactly finite full-power-set probability spaces)
Verification
Every X is independent of the trivial sigma-algebra: for A empty both sides of the rectangle identity are zero, and for A=Omega both equal . Thus [F1] gives the first formula. Since X is F-measurable, the known-variable clause of [F1] gives the second.
For example take two atoms a,b of masses using [F2], and X(a)=0, X(b)=4. Then . Under trivial conditioning the version has values (3,3), with integral 3 on Omega; under full conditioning it has values (0,4), with integrals 0 on {a} and 3 on {b}. These verify the two formulas numerically.
Source notes
Durrett Examples 4.1.3–4.1.5, printed pp.207–208; van der Vaart Examples 1.4–1.5, printed p.2.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
12 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Durrett, Probability: Theory and Examples, 5th ed. (standard reference, not scraped)