Statistics = Mathematized Epistemology

Evolution Of A Protest by Singularity Institute

Episode notes

1. Core Claim: Statistics = Mathematized Epistemology

- David Salsburg (The Lady Tasting Tea) — statistics emerged to formalize how we know what we know.

- E.T. Jaynes (Probability Theory: The Logic of Science) — probability is “extended logic,” turning uncertainty into rational belief.

- Key idea: epistemology becomes operational when expressed as likelihoods, priors, and updates.

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2. Statistics Doesn’t Lie — People Do

- Nate Silver (The Signal and the Noise) — misuse, not math, creates false certainty.

- John Ioannidis (“Why Most Published Research Findings Are False”) — incentives distort statistical practice.

- Examples:

- Cherry‑picking endpoints in drug trials.

- Misleading graphs in political polling.

- “P‑hacking” in academic research.

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