Experimental Design & Statistics

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75 primes originate from Experimental Design & Statistics and 71 more draw from it as a secondary origin — sort the Origin column to separate them. They span 69 subdomains; sort by that column to group them, or click any subdomain to filter to it.

Prime	Origin	Subdomain	Description
Access Control	Also draws from	—	Restrict system access.
Affordance	Also draws from	—	An action possibility offered by the fit between an agent and its environment.
Aggregate-Marginal Divergence	Primary	Aggregate vs Marginal Dynamics	The aggregate trends one way while the next unit's contribution trends the other.
Aggregation	Primary	Experimental Design	Deliberately collapsing many items into a single summary, choosing which information to discard to gain tractability.
Aliasing	Also draws from	Signal ProcessingControl Systems	Sampling a signal below the rate its information content demands folds distinct high-frequency states onto identical low-frequency ones, fabricating false structure that masquerades as real signal.
Anomaly detection	Also draws from	Outlier DetectionData Mining	Anomaly detection compares observations with a declared baseline, model, or population, estimates the significance of their deviation, and flags sufficiently rare or discordant cases for review or action.
Apparent Variety Masks Shared Driver	Primary	Dependence and Factor Structure	Surface multiplicity overstates true independence when a hidden common driver couples the items.
Bayesian Updating	Primary	—	Update beliefs with evidence.
Bias	Primary	—	Systematic, directional error distinct from random noise.
Blinding	Primary	Experimental Protocol	Deliberately withholding a specific piece of information from a decision-maker so a downstream judgment cannot be contaminated by it — a targeted severance of a bias channel.
Blocking (In Experimental Design)	Primary	—	Group similar units.
Calibrated Rule versus Moving World	Also draws from	Distribution Shift	A rule, model, or policy fitted to a past distribution of the world degrades as the world it was calibrated on drifts away from that distribution.
Calibration	Primary	Experimental Design	Aligning a system's output to a trusted reference by measuring deviation, adjusting to reduce it, and monitoring for drift.
Causality	Also draws from	—	Cause-effect relationships.
Coincidence	Primary	—	A conjunction of events or circumstances that is experienced as notably aligned despite lacking an established causal connection.
Comparison	Also draws from	—	Place items in a shared frame along chosen dimensions to read off a relation between them.
Compression	Also draws from	—	Reduce redundancy.
Conditional Entropy	Also draws from	Shannon Information Theory	Measure the expected uncertainty that remains about a target after a specified context is known.
Confidence Annotation	Primary	Evidence and Inference	A graded warrant marker attached to a claim that travels with it and tells downstream consumers how much weight to place on it.
Confidence Intervals	Primary	—	Range of plausible values.
Confounding	Primary	—	Hidden variable interference.
Construct Validity	Primary	Measurement Theory	Whether a measurement procedure actually captures the theoretical construct it claims to, rather than a correlated but distinct surrogate, across a three-layer construct-proxy-signal gap.
Continuum (measurement)	Primary	—	Represent variation as admitting gradual quantitative transitions across an ordered range rather than only abrupt membership in discrete categories.
Control Sample	Primary	Causal Inference Experimentation	A deliberately matched comparator held alongside the case of interest so that the difference between them isolates the effect of the factor under test from the shared background.
Correlated-Source Attribution Failure	Primary	Identification and Estimation	When combined sources share underlying variation, joint inference stays strong while attribution to any individual source becomes unstable, sign-flipping, or arbitrary.
Counterfactual Subtraction	Primary	Causal Inference	An effect is estimated by subtracting a constructed baseline representing what would have obtained absent the intervention, so the inference rests on the baseline's credibility, not the arithmetic.
Counterfactuals	Also draws from	—	Alternate hypothetical scenarios.
Cromwell's Rule	Primary	Bayesian Inference	Never assign prior probability of exactly 0 or 1 to a contingent proposition, because multiplicative Bayesian updating can never move a belief away from those endpoints.
Cross-Dimensional Leakage	Primary	Measurement and Construct Validity	A single shared variance source contaminates multiple supposedly-independent output dimensions, inflating their apparent correlations above the true cross-dimensional signal.
Cross-Level Inference	Primary	Multilevel Inference	Carry a predicate, relationship, estimate, or explanation from one level of an organized system to another through a stated or assumed bridge whose preservation conditions determine whether the target claim is warranted.
Crossover Interaction	Primary	Factorial Models and Effect Modification	The same input moves an outcome in opposite directions across levels of a second condition, so neither factor has a context-free sign and a main-effect average can cancel the mechanism to zero.
Data collection	Primary	—	Deliberately acquire and record observations about defined variables, events, texts, or experiences under a protocol that preserves provenance, quality, and fitness for a stated question.
Degrees of Freedom	Also draws from	—	Independent parameters.
Delphi Method	Also draws from	—	Expert consensus iteration.
Design for Lifecycle Adaptability	Also draws from	—	Plan for change.
Dimension	Also draws from	—	Degrees of freedom in a system.
Dimensionality Reduction	Primary	—	Reduce variables.
Distributional Assumption	Primary	Statistics	Commitment to assume uncertain quantities follow specific distribution.
Dose-Response Relationship	Also draws from	—	Input-output mapping.
Effect Size	Primary	—	Magnitude of effect.
Efficient Market Hypothesis (EMH)	Also draws from	—	Prices reflect info.
Elicitation Channel Contribution	Primary	Measurement Methodology	The recorded representation of a system's unobserved state is a joint product of state and the elicitation channel, so the analyst's marginal of interest is recoverable only by controlling the channel.
Ensemble	Also draws from	—	Multiple comparable realizations are generated or assembled and analyzed together through a probability model and aggregation rule to characterize a distribution rather than a single trajectory.
Error Proofing (Poka-Yoke)	Also draws from	—	Error prevention.
Estimation	Primary	—	Derive a usable value, range or state for an unknown quantity from incomplete, noisy or indirect information, with assumptions, uncertainty and decision purpose made explicit.
Expected Value	Also draws from	Probability Theory	Average a random quantity against its probability measure: the resulting linear functional compresses a distribution to its first moment while discarding dispersion, tails, and other shape.
Experimental Design	Primary	Experimental Design	Structuring an investigation through deliberate intervention, controlled assignment, and measurement so that causation can be distinguished from mere correlation and confounding.
Exposure-Distribution Learning	Also draws from	Frequency Learning	Exposure-distribution learning updates an internal model toward the empirical frequencies an agent repeatedly encounters, so the model tracks the exposure distribution rather than the target environment whenever the two distributions differ.
Extrapolation Beyond Sampled Regime	Primary	External Validity	A calibrated apparatus is deployed against inputs outside the regime its calibration was established in, while continuing to report the same confidence indicators it would report inside the regime, so its own self-reporting is structurally blind to the regime exit.
Extreme Capture Probability	Primary	Finite Population Sampling	When valuable targets are rare in a large heterogeneous population, a bounded untargeted sample captures them according to its coverage fraction — only n/N for the single best — so expanding reach or targeting matters more than prestige within the same bounded pool.
Factorial Design	Primary	—	Multiple variables tested together.
Fading	Also draws from	Education	Gradual withdrawal of instructional support as competence grows.
False Positive Paradox	Primary	Bayesian Inference and Screening	Under a rare base rate, most positive flags are wrong even when the detector is highly accurate.
Falsifiability	Also draws from	Philosophy of Science	A claim is scientific only if it could in principle be empirically refuted.
Figure-Ground	Also draws from	—	Perceptual organization of a field into salient figure and receding ground.
Foreseeing (Prediction)	Also draws from	—	Predict future states.
Gestalt Principles	Also draws from	—	Perceptual grouping rules.
Heavy-Tailed Distributions	Primary	Statistics Probability	Distributions where rare, extreme events carry most of the weight.
Hypothesis Testing (Null vs. Alternative)	Primary	—	Null vs alternative evaluation.
Identifiability	Primary	Causal Inference and System Identification	Whether an internal unknown can in principle be uniquely recovered from the observable signal a system makes available.
Impartiality	Also draws from	Political Philosophy	Treatment that depends only on relevant features and is invariant under the identity of the party involved.
Indirection	Also draws from	—	Introduces intermediary references.
Inductive Reasoning	Also draws from	—	Specific to general inference.
Inspection Paradox	Primary	Sampling Theory	When sampling proceeds by encountering items rather than enumerating them, longer items are over-represented in proportion to their length.
Instrument Interpretive Drift	Primary	Measurement and Metrology	A measurement instrument's interpretive practice silently shifts over time while its stated specification stays fixed, contaminating longitudinal trends.
Intervention	Primary	Causal Inference	Externally fixing a variable's value, severing its normal upstream causes while retaining its downstream effects.
Legibility	Also draws from	State Capacity and Administration	A distant actor makes heterogeneous local reality governable by projecting it into standardized, simplified representations, gaining comparison and control while discarding context the scheme cannot see.
Markov Blanket	Primary	Probabilistic Graphical Models	The minimal set of variables that, once observed, render a target conditionally independent of everything else — the system's statistical interface with its environment.
Mastery Learning	Also draws from	—	Ensure full understanding.
Measurement	Primary	Measurement Theory	Mapping a target's attribute onto a scale via an instrument and procedure, yielding a value-plus-uncertainty tied to a unit and frame.
Measurement Uncertainty and Observational Noise	Primary	Experimental Design	Measurement noise arises from instrument and observation limits.
Minimalism in Art	Also draws from	—	Reduce to essentials.
Minimum Viable Product (MVP)	Also draws from	—	Minimum viable product.
Missing Data Mechanisms (MCAR, MAR, MNAR)	Primary	—	MCAR, MAR, MNAR.
Model Assumption Failure	Also draws from	Modeling and Decision Support	A conclusion, forecast, or plan loses warrant when a load-bearing condition its model treated as true is false or ceases to hold, even if the reasoning inside the model remains correct.
Monte Carlo Simulation	Primary	—	Random sampling approximation.
Multiple Comparisons Correction	Primary	—	Adjust the thresholds or p-values of a defined family of simultaneous tests so a chosen family-level error criterion remains bounded despite multiplicity.
Multiplicative Random Growth	Also draws from	Probability and Stochastic Processes	Independent proportional shocks compound a positive state multiplicatively, so its logarithm follows an additive random walk and, under finite-variance increments, its cross-sectional distribution tends toward log-normal.
Necessity and Sufficiency	Also draws from	Logic	Separates what an outcome requires from what guarantees it, and joins both directions only when each condition exactly characterizes the other.
No Free Lunch Theorem	Also draws from	Optimization and Search	Averaged over all problem instances, no search, optimization, or learning procedure outperforms any other; a method's value is the match between its inductive bias and the problems it faces.
Nonparametric Methods	Primary	—	Distribution-free analysis.
Observational Equivalence	Also draws from	Philosophy of Science	Different internal systems are observationally equivalent when a declared observation regime cannot distinguish their outcomes.
Ornamentation	Also draws from	—	Decorative enhancement.
Outlier Leverage	Primary	Regression Diagnostics	A small number of extreme observations carry disproportionate weight in an aggregate result, so the result is more a property of those few points than of the bulk of the data — a consequence of the aggregation rule's non-resistance to extremes, not of any sampling defect.
Overfitting	Primary	—	Poor generalization.
Paradox of Unanimity	Primary	Bayesian Evidence Aggregation	Agreement beyond what independent observation could produce becomes evidence against the conclusion, signaling a broken-independence failure mode.
Parsimony (Occam's Razor)	Also draws from	—	Prefer simplicity.
Permutation	Also draws from	Combinatorics and Group Theory	Reassign every member or position of a collection exactly once, preserving membership while changing arrangement; the resulting bijective self-maps compose, invert, and decompose into cycles.
Poisson Process	Primary	Stochastic Processes	The structural skeleton of memoryless, independent arrivals at a constant average rate, serving as both null model and diagnostic coordinate system.
Prediction Error	Primary	Forecasting and Model Diagnostics	The signed discrepancy between a model-generated prediction and its realized observation becomes an operational signal for updating, routing through, or diagnosing the predictor.
Price Elasticity	Also draws from	—	Sensitivity to price changes.
Primary vs. Secondary Sources	Also draws from	—	Firsthand vs analysis.
Probability	Also draws from	—	Quantifies uncertainty and likelihoods.
Proxy–Target Fidelity	Primary	Construct Measurement	How faithfully an observable proxy tracks the unobservable target it stands in for — the degree to which acting on, optimizing, or inferring from the proxy is acting on the target itself.
Qualitative property	Primary	—	A property records kind, state or category without its identity depending on a numerical magnitude or arithmetic distance.
Randomization	Primary	—	Assign by chance.
Randomness	Also draws from	—	Model unpredictability.
Regression to the Mean	Primary	—	Extremes return toward average.
Relative Change	Also draws from	RatiosArithmetic	Relative change measures a quantity's difference from a declared reference value as a ratio to that reference, preserving proportional change while suppressing absolute scale.
Reporting-Pyramid Undercount	Primary	Surveillance and AscertainmentSafety Engineering	A true event population passes through ordered, non-random reporting filters whose layerwise capture rates multiply, so the recorded count is a biased fraction and changes in any filter can masquerade as changes in incidence.
Representational Modality	Also draws from	Communication Design	Choice of medium fundamentally shapes what can be expressed.
Reproducibility & Replicability	Primary	—	Repeatable results.
Research	Also draws from	Philosophy of ScienceResearch Methodology	Research is a creative and systematic inquiry that gathers, organizes, tests, and interprets evidence to increase warranted understanding while exposing its questions, methods, and sources of error to scrutiny.
Researcher Degrees of Freedom	Primary	Research Validity	The unpinned analytic choices between a question and a reported result, where a silently explored decision tree collapses into a single declared comparison, inflating false confidence without any individual choice being made in bad faith.
Residual Analysis	Primary	Model Diagnostics	Subtract the best explanation and study the leftover as the next site of structure, not as noise.
Responsibility Diffusion	Also draws from	Organizational Behavior	Spreading responsibility reduces individual accountability perception.
Reverse Engineering	Also draws from	—	Analyze existing systems.
Reversibility and Irreversibility	Also draws from	Decision Theory	Actions or transitions may or may not be undone or reverted.
Reversibility Horizon	Also draws from	Decision Analysis	Temporal threshold where reversal cost exceeds forward commitment.
Rhythm	Also draws from	Music	Patterned recurrence of elements across time or space.
Robustness	Also draws from	—	Maintain functionality under stress.
Sampling (Representativeness)	Primary	—	Representative subset selection.
Scaling and Scale Dependence	Also draws from	Systems Science	Patterns and constraints change qualitatively across different scales.
Segmentation and Boundary Drawing	Also draws from	—	Partitioning continuous domain via boundaries concentrates meaning.
Selection	Also draws from	Set and Population Operations	From an available population, a criterion, pressure, or rule gives some alternatives greater retention, passage, or weight than others, producing a survivor set or shifted composition.
Selection Bias	Primary	—	Skewed sampling.
Selection on Noisy Estimates	Primary	Selective InferenceMachine Learning	When noisy estimates help determine which candidates, results, or options are selected, conditioning on selection shifts the selected estimates toward the favored tail and makes them systematically overstate their latent values.
Selective Information Severance	Primary	Bias ControlPrivacy	Deliberately cutting an information channel on a need-to-know basis, so a party cannot act on, be biased by, or leak information it never receives.
Sensitivity Analysis (in Operations Research)	Also draws from	—	Analyze impact of parameter variation.
Silence as Signal	Primary	Missing Data	Cost-asymmetric record production makes absence misread as the negative state.
Similarity Measure	Also draws from	Measurement TheoryInformation Retrieval	Map an ordered pair, under a declared representation and relevance rule, to a comparable degree of likeness; the score may be nonmetric or asymmetric, and changing the frame can reverse what counts as near.
Simpson's Paradox	Primary	Causal Inference	A relationship can run one direction inside every subgroup and the opposite direction in the aggregate, because a confounder's distribution differs across subgroups and is silently mixed away on pooling.
Simpson–Yule Effect	Primary	—	An association measured in pooled data can reverse, vanish, or appear once the data are partitioned by a confounder unevenly distributed across the compared groups.
Specialization	Also draws from	—	Agents concentrate on a narrow range of tasks for efficiency.
Stationarity	Primary	—	Stable statistical properties.
Statistical Inference	Primary	Experimental Design	Reasoning from a finite, noisy sample back to the underlying population or process while explicitly quantifying the uncertainty that sampling introduces.
Statistical Power	Primary	—	Probability of detecting effect.
Statistical Significance (p-Value)	Primary	—	Likelihood results are random.
Statistical syllogism	Also draws from	—	Project a qualified proportion from a declared reference class onto a particular member as defeasible support for that member's having the attribute, with inferential strength inherited from the proportion and revised when a more relevant class or case-specific fact becomes available.
Streetlight Effect	Also draws from	Methodology of Inquiry	Search effort concentrates where evidence is easiest to observe rather than where the sought answer is most likely to lie, systematically substituting accessibility for relevance.
Subadditivity	Also draws from	Analysis and Inequalities	A combined whole never evaluates above the sum of its separately evaluated parts, so decomposition supplies a guaranteed upper bound.
Substitutability	Also draws from	Systems Engineering	One component replaces another without functional degradation.
Texture	Also draws from	—	The fine-grained surface variation beneath an object's gross form that carries perceptual, material, and emotional information rather than mere decoration.
Transferability Overclaim	Primary	External Validity	A result established under specific scope conditions is exported beyond them with those conditions stripped, so the claim arrives at its new site shorn of the limits that made it true.
Triangulation	Also draws from	—	Cross-verifying a claim by combining multiple independent sources or methods so their convergence raises confidence and their divergence exposes hidden bias or context.
Truncation	Also draws from	—	Apply a declared boundary to retain an admissible bounded part of an ordered, extended, or over-complete object while discarding the part that lies beyond it.
Type I & Type II Errors	Primary	—	False positive/negative.
Uncertainty	Also draws from	—	Incomplete knowledge.
Underspecification	Primary	Model Identification	A selection process treats evidence as if it picked out a single answer when many distinct answers fit it equally well, so a hidden closure silently chooses one representative and the behavior that distinguishes them is left uncontrolled.
Unit of measurement	Primary	—	A conventionally fixed reference magnitude that makes quantities of the same kind expressible as comparable numerical multiples.
Unity & Variety	Also draws from	—	Balance between consistency and diversity.
Validation	Primary	Experimental Design	Confirming that an artifact actually solves the intended problem in its real operational context, as distinct from confirming it was merely built to specification.
Value of Information	Also draws from	Decision Analysis	Measure evidence by how much having it before acting is expected to improve the best available decision, relative to acting now and net of the cost of obtaining it.
Variability	Primary	—	Differences across instances.
Verification	Also draws from	—	Check that an object conforms to its specification via a defined procedure yielding evidence and a verdict.
Wisdom of the Crowds	Also draws from	—	Many independent noisy signals combine into an estimate better than any individual (information aggregation).