Reusable cognitive primitives
Probability
A way to reason about uncertainty by assigning each possible outcome a share of the whole, between impossible (0) and certain (1).
- Blaise Pascal — Co-founded · 1654
- Pierre de Fermat — Co-founded · 1654
The mathematical theory of probability grew out of the 1654 correspondence between Pascal and Fermat on games of chance.
Sources: MacTutor History of Mathematics Archive, Encyclopaedia Britannica
Where it appears
Dependencies & synergies
Derived from the graph’s real structure — 22 concepts across 27 disciplines carry this pattern. Every figure is a count, not a score.
How many concepts carrying this pattern are seen through each discipline.
Other thinking patterns that recur on the same concepts — the more shared concepts, the more often they co-occur.
What kinds of relationships the carrying concepts form — the relational signature of the pattern.
Concepts where this pattern does the most cross-disciplinary work — each reaches disciplines beyond its own.
- Machine learningreachesAlgorithmsBiochemistryBiologyBiotechnologyBusinessCognitive ScienceData ScienceDesignDiscrete MathematicsEconomicsEducationEducational ScienceEngineeringEvolutionary BiologyHuman-Computer InteractionLogicMathematical ModellingMathematicsNeuroinformaticsNeuroscienceOptimizationProbabilitySoftware EngineeringSystems BiologySystems EngineeringSystems ScienceTheory of Computation
- ProbabilityreachesActuarial ScienceArtificial IntelligenceBiostatisticsComplexity ScienceComputer ScienceData ScienceDecision TheoryDiscrete MathematicsEconomicsEpistemologyEthicsFinanceInformation TheoryMachine LearningMedicinePhysical ChemistryPhysicsPublic PolicyQuantum PhysicsStatistical PhysicsThermodynamics
- RiskreachesActuarial ScienceBusinessData ScienceEntrepreneurshipEnvironmental ScienceEpidemiologyEpistemologyMachine LearningMathematicsNetwork SciencePhotographyProbabilityPublic HealthToxicology
- CorrelationreachesBiostatisticsEconometricsEconomicsEpidemiologyEthicsFinanceHistoryMathematicsMedicineMetaphysicsPhilosophy of SciencePsychologyPublic Policy
- PredictionreachesBiologyCognitive ScienceComputer ScienceData ScienceEducational ScienceEpistemologyHistory of ScienceLogicMachine LearningMathematical ModellingPhysicsSystems Science
- GeneralizationreachesArtificial IntelligenceComputer ScienceData ScienceEducationEducational ScienceLinguisticsLiteratureMathematicsPhilosophyPhilosophy of Science
Carrying concepts that others in the same pattern build on (they depend on or follow from these).
- Probability — 5 other concepts build on it
- Probability distribution — 2 other concepts build on it
Examples across disciplines
A weather forecast of 30% rain means: on days that look like this, it rains about three times in ten.
We cannot say where one gas particle is, but probability describes the behaviour of trillions together.
A screening test's result shifts the probability that a patient has a condition; it rarely proves it outright.
How this pattern travels
Interpreted from where the pattern recurs in the atlas — structural transfer and coverage, not a claim it is universally the "best" model.
Recurs across 27 disciplines over 22 carrier concepts — a broadly transferable pattern.
structural · Structural recurrence in the atlas — a pattern is a reasoning lens, not a law.
7 of its 22 carrier concepts are themselves cross-disciplinary connectors.
structural · Structural recurrence in the atlas — a pattern is a reasoning lens, not a law.
Coverage matrix
How these concepts distribute across domains and concept families — real counts, not a score.
Knowledge timeline
Real, sourced key dates of these concepts.
- 1866Mendelian inheritance · Publication · Biology
- 1896Radioactive decay · Discovery · Physics
- 1900Quantum mechanics · Publication · Physics
- 1944Game theory · Publication · Economics
- 1950Game theory · Formalization · Economics
The statistical fingerprint
How the 22 concepts that exercise this pattern distribute — from the graph, not a ranking.
Disciplinary fingerprint
Carrier concepts under each illuminating lens.
How settled its carriers are
Epistemic status of the concepts that exercise this pattern.
✕ That past independent results (like coin flips) change what is 'due' to happen next.
Journeys where it shows up
You have seen this model in one place. Where else could it apply — and where would the analogy break?
Correlation →Instead of 'will it happen?', ask 'how often would it happen if this repeated many times?'
- Recurs across 27 disciplines.
- 65 concepts exercise this thinking pattern.
- It is practised in 1 learning journey.
Derived from the graph — a pattern is a reasoning lens, not a law.
Instead of 'will it happen?', ask: across many repetitions what share would turn out this way — and how much of what I see could be chance?
Keep this question handy when you meet something new — it helps you notice the pattern, not just name it.