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.
Chebyshev's inequality on a finite probability space
Statement
For every finite real random variable and every , Equivalently, if and , then . If , the first form remains valid for every .
Facts & Assumptions
Given: A finite real random variable and a real threshold .
Variance is and (Variance, standard deviation, and covariance on a finite probability space).
Markov's inequality states for nonnegative and (Markov's inequality on a finite probability space).
Proof
The variable is nonnegative, and for the events and are equal.
Apply [L2] to at the positive threshold and use [L1] to obtain the first inequality.
If , substitute in step 2.1 and cancel to obtain . Conversely, given , choose in the standard-deviation form to recover step 2.1. If , step 2.1 gives probability at most zero for every .
Depends on
Used by
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 24 results over 7 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- C. M. Grinstead and J. L. Snell, Introduction to Probability, 2nd ed., Theorem 8.1 (standard reference, not scraped)
- H. Pishro-Nik, Introduction to Probability, Statistics, and Random Processes, Section 6.2.2 (standard reference, not scraped)