Probability
The branch of mathematics that measures how likely uncertain events are, expressed as a number between 0 and 1.
A discipline is a lens, not an owner — the same idea can be viewed through many.
Concepts viewed through this lens
These numbers describe the current Thinking OS knowledge slice, not the whole field.
Disciplines it bridges to
Each bridge is built by ideas the two fields share, the thinking patterns that recur across both, and a representative relationship that shows how they connect.
Probabilityconnects toMathematics
Shared thinking patterns
Why this bridge exists
Combinatorics enables Probability — combinatorics enables Probability.
Explore this connection →Probabilityconnects toStatistics
Shared concepts
Shared thinking patterns
Why this bridge exists
Histogram models Probability distribution — histogram models probability distribution.
Explore this connection →Probabilityconnects toMedicine
Shared thinking patterns
Why this bridge exists
Risk depends on Probability — Judging risk depends on probability.
Explore this connection →Probabilityconnects toEconomics
Shared thinking patterns
Why this bridge exists
Game theory depends on Probability — game theory depends on Probability.
Explore this connection →Probabilityconnects toEpistemology
Shared concepts
Shared thinking patterns
Why this bridge exists
Correlation is commonly confused with Causation — Correlation is commonly confused with causation.
Explore this connection →Probabilityconnects toFinance
Shared thinking patterns
Why this bridge exists
Risk depends on Probability — Judging risk depends on probability.
Explore this connection →Probabilityconnects toPhysics
Shared thinking patterns
Why this bridge exists
Experiment suppresses Confounding variable — A controlled experiment holds confounders fixed.
Explore this connection →Probabilityconnects toBiostatistics
Shared thinking patterns
Why this bridge exists
Regression analysis models Correlation — regression analysis models Correlation.
Explore this connection →
Field shape — representation health
76/100 overall · 7 concepts
The eight dimensions measure Thinking OS coverage of this field, not the quality or importance of the discipline.
What kind of structure is this field?
Interpreted from the current atlas — how this field is represented, not a judgement of the field.
Representation health 76/100 — healthy representation. Strongest: cross-disciplinary, taxonomy. Thinnest: factual depth.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
81% of its relations reach into 31 other disciplines — an outward-facing field in the atlas.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
Its 76 representation-health is above the 54 median of 139 similarly-sized disciplines (comparable by concept count).
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
14% of its concepts have a single connection (mean internal degree 1.7) — a fairly cohesive internal structure.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
Current atlas gaps: no dated concepts.
atlas representation · Measures the current Thinking OS representation, not the quality or importance of the field.
How this lens connects
The kinds of relationship that characterise this discipline lens in the current slice.
Coverage matrix
How these concepts distribute across domains and concept families — real counts, not a score.
Ideas that connect this discipline outward
Concepts viewed through this lens that reach disciplines it does not itself carry — concept-level bridges (distinct from the discipline-to-discipline bridges below).
- ProbabilityreachesActuarial ScienceArtificial IntelligenceBiostatisticsComplexity ScienceComputer ScienceData ScienceDecision TheoryDiscrete MathematicsEconomicsEpistemologyEthicsFinanceInformation TheoryMachine LearningMedicinePhysical ChemistryPhysicsPublic PolicyQuantum PhysicsStatistical PhysicsThermodynamics
- CorrelationreachesBiostatisticsEconometricsEconomicsEpidemiologyEthicsFinanceHistoryMathematicsMedicineMetaphysicsPhilosophy of SciencePsychologyPublic Policy
- Confounding variablereachesBiologyData ScienceEpistemologyHistory of SciencePhilosophy of SciencePhysics
- Probability distributionreachesPhotographyTelecommunications Engineering
- Random variablereachesAlgebraStatistics
Mental models that recur here
Probability ×6
A way to reason about uncertainty by assigning each possible outcome a share of the whole, between impossible (0) and certain (1).
Cause and effect ×2
One thing genuinely bringing about another — as opposed to two things merely moving together. Establishing it needs a mechanism and controls, not just a pattern.
Signal vs noise ×1
Real data mixes a meaningful pattern (signal) with random variation (noise); the skill is telling them apart before you act on either.
People represented in this atlas
People tagged with this lens who have a recorded contribution. Not exhaustive, and not a ranking.
- Pierre de Fermat
1607–1665
- Blaise Pascal
1623–1662
- Thomas Bayes
1701–1761
- Pierre-Simon Laplace
1749–1827
- Carl Friedrich Gauss
1777–1855
- 7 concepts are viewed through this lens.
- 5 of them bridge into other disciplines.
- Its signature thinking pattern is “Probability” (recurs in 6 concepts).
- The most common kind of connection here is “Teaching link”.
- It is most tightly linked to Mathematics.
Derived from the current graph structure — observations, not a judgement of the field.