Thinking·OS

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Explore the knowledge graph

Actuarial science applies to Probability. Activate to inspect this relation.Actuarial science applies to Risk. Activate to inspect this relation.Average applies to Probability distribution. Activate to inspect this relation.Bayesian inference applies to Probability. Activate to inspect this relation.Biostatistics applies to Probability. Activate to inspect this relation.Combinatorics enables Probability. Activate to inspect this relation.Entropy depends on Probability. Activate to inspect this relation.Expectation is analogous to Average. Activate to inspect this relation.Expectation depends on Probability distribution. Activate to inspect this relation.Histogram models Probability distribution. Activate to inspect this relation.Lindy Effect applies to Probability. Activate to inspect this relation.Markov chain applies to Probability. Activate to inspect this relation.Matthew Effect applies to Probability. Activate to inspect this relation.Machine learning depends on Probability. Activate to inspect this relation.Normal distribution is a Probability distribution. Activate to inspect this relation.Probability measures Correlation. Activate to inspect this relation.Probability distribution depends on Probability. Activate to inspect this relation.Quantum mechanics depends on Probability. Activate to inspect this relation.Random variable depends on Probability distribution. Activate to inspect this relation.Risk is analogous to Correlation. Activate to inspect this relation.Risk depends on Probability. Activate to inspect this relation.Sampling applies to Probability distribution. Activate to inspect this relation.Standard deviation depends on Variance. Activate to inspect this relation.Variance measures Probability distribution. Activate to inspect this relation.VarianceProbability distributionStandard deviationProbabilityNormal distributionExpectationRandom variableAverageHistogramSamplingRiskCorrelationMachine learningQuantum mechanicsEntropyActuarial scienceBayesian inferenceBiostatisticsCombinatoricsLindy EffectMarkov chainMatthew Effect
Relationship types

34 concepts viewed through this lens. Bridge concepts connect this view to Actuarial Science, Algorithms, Artificial Intelligence, Atmospheric Science….

Legend
  • Focused concept
  • Connected concept
  • Bridge concept (just outside the lens)
  • Arrow points from cause / source to effect / target
  • A line with no arrow is a two-way relationship
  • Node colour marks the concept’s primary discipline
22 concepts24 relationships25 disciplines6 relation families

At a glance

In probability theory and statistics, variance is a measure of dispersion, meaning it is a measure of how far a set of numbers are spread out from their average value.

Disciplines
Mathematics · Statistics
Role in the graph
Connector
Relationships
2 · 2 relation families
Mental models
1

What am I looking at?

In this lens (34)

Bridge concepts (68)

Just outside the lens — they connect it to other context.

  • Experiment4
    Biology, History of Science, Philosophy of Science, Physics · connects to Confounding variable, Evidence, Hypothesis…
  • Supervised learning4
    Computer Science, Data Science, Machine Learning · connects to Generalization, Machine learning, Prediction…
  • Actuarial science2
    Actuarial Science, Finance · connects to Probability, Risk
  • Expectation2
    Mathematics, Probability · connects to Average, Probability distribution
  • Exposure2
    Environmental Science, Photography, Public Health, Toxicology · connects to Histogram, Risk

Insights from this view

Structural observations about the concepts shown here — descriptions of this graph, not claims about the world.

  • This view connects 25 disciplines: Actuarial Science, Artificial Intelligence, Biostatistics, Computer Science, Data Science, Decision Theory, Discrete Mathematics, Economics, Epistemology, Ethics, Finance, Information Theory, Machine Learning, Mathematics, Medicine, Photography, Physical Chemistry, Physics, Probability, Public Policy, Quantum Physics, Statistical Physics, Statistics, Telecommunications Engineering, Thermodynamics.
  • Variance is a bridge concept — viewed here through Mathematics, Statistics.
  • The connections here span 6 relation families.
  • Probability explains 11 concepts in this view (Artificial Intelligence, Computer Science, Data Science, Discrete Mathematics, Economics, Epistemology, Ethics, Finance, Machine Learning, Mathematics, Medicine, Physics, Probability, Public Policy, Quantum Physics, Statistics, Telecommunications Engineering).

Relationships as a list

The focused concept’s relationships. Pick another concept in the graph above to update this list.

Explore through a different lens

A lens is a deterministic projection of the graph. Pick a discipline, thinking pattern or journey to reframe the whole view.

By discipline

ChemistryBiologyPhysicsMathematicsComputer ScienceGeologyMineralogyEconomics

By thinking pattern

Bayesian updatingCause and effectCompoundingConservationConstraintsDefense in depthDiffusion & spreadEmergenceEnergy transformationEntropy & irreversibilityEquilibriumFeedback loopIncentivesInformationLevels & hierarchyModularityNetworksOptimizationOscillationProbabilityRecursion & self-similarityScaleSignal vs noiseSource–pathway–receptorStocks and flowsSymmetry & invarianceThresholds & tipping pointsTrade-offsTriangulationVariation & selectionWaves

By journey

From a Leaf to the ClimateWhy Music Moves UsHow Machines LearnReasoning about a Leaf and the Climate

Concept collections

Concept collections are curated lenses onto the fabric — themed sets of ideas that recur across disciplines. They are not journeys; they are a way to read the graph.

About this view

What this is

Start from one concept and expand outward. The view never shows everything at once — click a node to refocus, filter by relationship type, or switch to an accessible list.

One fabric

3750 concepts and 5051 typed relations form one connected component — no isolated silo.

How to read it

Focus a concept, or apply a lens (discipline, mental model, journey) to see only the threads that matter.