Exercise 1: Applying Three Checklist Items to a Real Claim — Possible Solution
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This exercise has no single correct claim to analyze - the point is
applying the three named checks honestly to something real. A worked
example, using "coffee drinkers live longer":

STEP 1 - BREAK IT DOWN: The vague claim splits into more specific,
checkable sub-questions: how much coffee, over what time period,
compared to what baseline (non-drinkers, or moderate vs. heavy
drinkers), and "live longer" measured how (all-cause mortality? a
specific disease risk?).

STEP 4 - CAUSATION CHECK: Most real studies on this topic are
observational (people who already choose to drink coffee, not
randomly assigned to drink it), so a real, plausible confounding
variable exists: coffee drinkers may differ systematically from
non-drinkers in other health-relevant ways (income, overall diet,
smoking status, social patterns), any of which could independently
affect lifespan - meaning "coffee causes longer life" is a stronger
claim than most such studies can actually support on their own.

STEP 5 - BASE RATE CHECK: A claimed "X% lower risk" needs a real
underlying number to mean anything - a large relative risk reduction
applied to an already-rare outcome may represent a genuinely small
real, absolute difference, the same base-rate issue Chapter 5's own
disease-testing example demonstrated.

ANSWER: (worked example) For "coffee drinkers live longer" - breaking
it down reveals unspecified amounts, timeframes, and baselines;
checking causation reveals the underlying evidence is mostly
observational with real, plausible confounding variables (income,
diet, smoking); checking the base rate would require converting any
claimed relative risk reduction into a real absolute number before
judging how meaningful it actually is.

WHY THIS WORKS AS AN ANSWER
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This applies the three specifically named checklist items to a real,
concrete claim, using the exact reasoning techniques those chapters
established rather than a generic "it's complicated" response.