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Test factorial A/B×Experiment factorial×
CampDisseny experimentalDisseny experimental
FamíliaProcess / pipelineProcess / pipeline
Any d'origenFactorial design: 1920s–1930s; applied online as factorial A/B test: 2000s–2010s1926–1935
Autor originalRonald A. Fisher (factorial design); digital A/B testing popularized by Google, Microsoft, and Amazon in the 2000sRonald A. Fisher
TipusControlled online/field experimentQuantitative experimental design
Font seminalKohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press. ISBN: 978-1108724265Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
Àliesfactorial split test, multi-factor A/B test, factorial online experiment, factorial controlled experimentfactorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design
Relacionats66
ResumA factorial A/B test is a controlled online experiment that simultaneously manipulates two or more independent factors, each at two or more levels, exposing different user groups to every combination of factor levels. Rooted in Fisher's factorial design and operationalised at scale by tech companies, it enables researchers to estimate both the independent main effect of each factor and the interaction effects between factors — all from a single experimental run.A factorial experiment is an experimental design in which two or more independent variables (factors) are manipulated simultaneously, and every combination of their levels is tested. Introduced by Ronald Fisher in the 1920s–1930s, it is the standard approach whenever a researcher needs to detect not only the main effect of each factor but also whether the effect of one factor depends on the level of another — the interaction effect.
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ScholarGateCompara mètodes: Factorial A/B Test · Factorial Experiment. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare