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Factorial experiment — Wikipedia (en)

Source: Wikipedia (en)
Original: https://en.wikipedia.org/wiki/Factorial_experiment
License (as archived): CC-BY-SA-4.0
Archived: 2026-10-31T09:51:58.626Z
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Factorial experiment — Wikipedia (en) — Wikipedia (en), https://en.wikipedia.org/wiki/Factorial_experiment (CC-BY-SA-4.0); archived copy: https://metraipolis.com/documento/dc_4ebf737eb5bb (Metraipolis archive dc_4ebf737eb5bb, sha256 6ea78ac433fc7db989e7d724ba3357113f073733289584ac6754353e974e42b0)

BibTeX

@misc{dc4ebf737eb5bb,
  title = {Factorial experiment — Wikipedia (en)},
  howpublished = {Wikipedia (en)},
  url = {https://en.wikipedia.org/wiki/Factorial_experiment},
  note = {License CC-BY-SA-4.0; archived copy https://metraipolis.com/documento/dc_4ebf737eb5bb; sha256 6ea78ac433fc7db989e7d724ba3357113f073733289584ac6754353e974e42b0},
  year = {2026}
}

Archived text

Reproduced under CC-BY-SA-4.0. Attribution: Wikipedia (en), https://en.wikipedia.org/wiki/Factorial_experiment. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

In statistics, a factorial experiment (also known as full factorial experiment) investigates how multiple factors influence a specific outcome, called the response variable. Each factor is tested at distinct values, or levels, and the experiment includes every possible combination of these levels across all factors. This comprehensive approach lets researchers see not only how each factor individually affects the response, but also how the factors interact and influence each other. Often, factorial experiments simplify things by using just two levels for each factor. A 2x2 factorial design, for instance, has two factors, each with two levels, leading to four unique combinations to test. The interaction between these factors is often the most crucial finding, even when the individual factors also have an effect. If a full factorial design becomes too complex due to the sheer number of combinations, researchers can use a fractional factorial design. This method strategically omits some combinations (usually at least half) to make the experiment more manageable. These combinations of factor levels are sometimes called runs (of an experiment), points (viewing the combinations as vertices of a graph), and cells (arising as intersections of rows and columns).

Tema degli esploratori: statistica e scienza dei dati (deposito sistematico; ricerca «regression analysis»).
Fonte: Wikipedia in inglese, voce «Factorial experiment» — https://en.wikipedia.org/wiki/Factorial_experiment
Wikidata Q4116558: «experiment whose design consists of two or more factors, each with discrete possible values, and whose experimental units take on all possible combinations of these levels across all such factors» (dati Wikidata in CC0 1.0) — https://www.wikidata.org/wiki/Q4116558
Autori: i contributori di Wikipedia (cronologia: https://en.wikipedia.org/wiki/Factorial_experiment?action=history).
Licenza: Creative Commons Attribuzione-Condividi allo stesso modo 4.0 (CC BY-SA 4.0) — https://creativecommons.org/licenses/by-sa/4.0/. Il riuso richiede attribuzione e stessa licenza.
Estratto dell'introduzione non modificato nel contenuto; revisione 1374108839, consultata il 2026-10-31T09:38:27.250Z tramite l'API ufficiale di Wikipedia. Impronta SHA-256 dell'estratto: 2e919722319f4105f7de00ff074d6b82a47fd646094b85d9c6e8a2f085c7c7af