Probabilistic Thinking
Most performance choices are bets made with incomplete information, and this collection is about making those bets well.
It covers Bayesian updating, expected value, calibration and the overconfidence effect, asking how clearly people actually reason when outcomes are uncertain. As ever here, strong claims are checked against the research before they are recommended.
newest 24 Jul 2026
Most read here · Guide
Probabilistic Thinking: Reasoning Under Uncertainty With Bayesian Logic →
Editor's Pick · Probabilistic Thinking
The Overconfidence Effect: Why Experts Are Wrong More Often Than They Think
The science of overconfidence bias: experts at 98% confidence are right 68% of the time. Research on why certainty fails and how to calibrate judgment.
Deep dive · 18 Jun 2026
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Reading order
Measure yourself
Calibration Test: How Well-Calibrated Are Your Predictions?Get a baseline before you change anything. 20 questions; scored on real dimensions.
Read the evidence
The Overconfidence Effect: Why Experts Are Wrong More Often Than They ThinkThe full argument, chapter by chapter.
Apply it
90-Day Probabilistic Thinking Protocol: Build Bayesian IntuitionA written method to run: 12 weeks.
The complete shelf, unpaginated
Holdings
Deep Dives
Long-form investigations with full bibliographies.
The Overconfidence Effect: Why Experts Are Wrong More Often Than They ThinkThe science of overconfidence bias: experts at 98% confidence are right 68% of the time. Research on why certainty fails and how to calibrate judgment.Deep dive · 18 Jun 2026
The Placebo Effect: The Neuroscience of How Belief Physically Changes BiologyThe neuroscience of the placebo effect: how expectation activates opioids, dopamine, and endocannabinoids to produce measurable biological change. 27 sources.Deep dive · 18 Jun 2026
Guides
Structured, chaptered field manuals.Protocols
Multi-week programmes with a written method.
Assessments
Scored self-assessments with real question banks.
Glossary
Defined terms, each with its own entry.
Bayes' Theorem: Definition and How to Update Beliefs in Light of EvidenceBayes' theorem is a rule for revising probability estimates in light of new evidence. Learn the formula, base-rate neglect, and how to apply it.Glossary term · 18 Jun 2026
Prospect Theory: Kahneman & Tversky's Definition of How Humans Actually Weigh ProbabilityProspect theory describes how people evaluate outcomes relative to a reference point, with losses weighing roughly twice as heavily as equivalent gains.Glossary term · 18 Jun 2026
Antifragility: Taleb's Definition and Why Some Things Gain From DisorderAntifragility is the property of gaining capability from disorder, not just surviving it. Taleb's framework for systems that improve under stress.Glossary term · 17 Jun 2026
Black Swan: Taleb's Definition and the High-Impact Unpredictable EventA black swan is a rare, high-impact event outside normal probability models, rationalised as foreseeable only in hindsight. Coined by Nassim Taleb.Glossary term · 17 Jun 2026
Expected Value: Definition and the Probabilistic Decision RuleExpected value is the probability-weighted average of possible outcomes. The EV formula, how cognitive biases distort it, and professional applications.Glossary term · 16 Jun 2026
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Most read on this shelf
- Probabilistic Thinking: Reasoning Under Uncertainty With Bayesian LogicGuide
- The Overconfidence Effect: Why Experts Are Wrong More Often Than They ThinkDeep dive
- Calibration Test: How Well-Calibrated Are Your Predictions?Assessment
- The Placebo Effect: The Neuroscience of How Belief Physically Changes BiologyDeep dive
- AntifragilityGlossary term