spurious

Spurious is an adjective that describes something not genuine, valid, or true, or something appearing plausible but deceptive. The term comes from the Latin spurius, meaning illegitimate.

In science and statistics, spurious refers to relationships or results that seem real but are not caused by the proposed mechanism. A spurious correlation is a statistical association between two variables that arises from coincidence, a hidden confounding factor, or data artifacts rather than a causal link. Spurious regression is a phenomenon in time series where non-stationary data yield a misleading relationship despite lacking a true connection. Addressing spurious results involves careful study design, proper controls for confounding, and checks for nonstationarity.

In signal processing and electronics, spurious describes unwanted energy or responses. Spurious emissions are frequencies produced by a device beyond its intended signals, while a spurious response is an unintended signal generated by components such as mixers or filters. Specifications often reference spurious-free dynamic range (SFDR), which measures the suppression of these artifacts.

In everyday language, spurious can describe claims, documents, or products that are forged, counterfeit, or not genuinely representative of what they purport to be. Spurious evidence or arguments are those lacking credible support or misinterpreting data.

Overall, the concept of spurious highlights the distinction between legitimate, reproduciable phenomena and artifacts, coincidences, or forgeries. Detecting and mitigating spurious elements is central to reliable inference, measurement integrity, and rigorous evaluation across disciplines.