tufte-data-forensicslisted

# Data Forensics: Auditing an Analysis Before You Trust It ## Overview *Seeing With Fresh Eyes* ch. 4 (printed **pp. 80–119**) is a procedure, not a lament. Its organizing device is a proposed reference work — an imagined *Data Measurement and Analysis: 1,000 Safeguards, Pitfalls, and Cheats in Statistical Practice*, modeled on Khonsari and Sintek's cardiac-surgery encyclopedia of some 3,000 graded alerts and warnings (p. 82). The parallel is the whole argument: surgery already has an itemized, severity-graded, actionable literature of things that go wrong at the point of work, and statistical practice does not — even though a botched analysis reaches more lives than a botched operation. This skill owns the **step-by-step audit**. Two siblings own adjacent material and are not repeated here: | Sibling | Owns | |---|---| | `tufte-evidence-corruption` | The catalog of corruption *types* — cherry-picking, effects without causes, model searching, overreaching, chartjunk, the rage to conclude, Chalmers, the "Which half?" exchange | | `tufte-visual-thinking` | The seeing discipline and the ch. 4 *highlights* — Feynman/Mosteller, statistical vs. named lives, sampling-to-please, the Lucent triad, forensic-audit-vs-cleaning as named concepts | What follows turns those named concepts into an executable audit: what to look at, in what order, what to demand, and what to write down. **The operating stance.** Feynman's rule opens the chapter's facing page: the first principle is that