The closeness of a measurement or estimate to the actual, accepted, or true value of the quantity measured; a property concerned with systematic error or bias rather than with random spread.

Principle

Accuracy depends on bias and calibration: reducing systematic error or aligning measurement to a known reference increases accuracy; accuracy can be assessed by comparison to an accepted standard or true value when available.

Demonstration

Illustrative scenario → Situation: a temperature sensor is calibrated against a certified reference and then used to measure a known reference sample. Recognition: the mean measured value lies within specified tolerance of the reference. Action: accept sensor as accurate for the intended range. Consequence: subsequent measurements, averaged appropriately, are likely to reflect true temperature within stated limits, provided calibration holds.

Misapplication

Inferring accuracy from a single measurement or from small-sample agreement: the error is assuming one or few matches guarantee absence of systematic bias without adequate reference or repeated checks.

Consequence

Accurate measurements are necessary for valid inference, comparability across studies, and correct decisions that depend on true values; lack of accuracy can produce systematically incorrect conclusions even when measurements are precise.

Reversal

When no agreed external reference or true value exists (e.g., some constructs in social science), 'accuracy' must be qualified as conformity to an operational definition or consensus standard rather than literal trueness.

Boundary

Clearly within: measurements compared against a traceable standard or known physical quantity. Boundary case: proxy measures that approximate a target concept—may be accurate for some purposes but not literally equal to the target. Clearly outside: purely subjective judgments without an external standard of truth.

Semantic Tension

Accuracy ↔ Precision: improving one does not guarantee the other; both are distinct dimensions of measurement quality.

Synthesis

Accuracy captures systematic correctness (trueness) relative to a reference; reliable measurement practice requires both control of bias (accuracy) and control of variability (precision).