ScholarGate
Assistente

Comparar métodos

Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Teste A/B Fatorial×Experimento Fatorial Completo×
ÁreaDelineamento experimentalDelineamento experimental
FamíliaProcess / pipelineProcess / pipeline
Ano de origemFactorial design: 1920s–1930s; applied online as factorial A/B test: 2000s–2010s1926 (Fisher's foundational paper); codified by the 1950s–1960s
Autor originalRonald A. Fisher (factorial design); digital A/B testing popularized by Google, Microsoft, and Amazon in the 2000sRonald A. Fisher
TipoControlled online/field experimentExperimental design
Fonte seminalKohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press. ISBN: 978-1108724265Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130
Outros nomesfactorial split test, multi-factor A/B test, factorial online experiment, factorial controlled experimentfull factorial design, complete factorial design, 2^k factorial design, FFD
Relacionados66
ResumoA 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 full factorial experiment runs every possible combination of all chosen factor levels, making it the gold standard for simultaneously estimating main effects, two-way interactions, and higher-order interactions among multiple independent variables. Introduced through Ronald Fisher's foundational work on factorial designs in the 1920s and systematised by Box, Hunter, and Montgomery, it provides complete information about how factors act individually and in combination on an outcome.
ScholarGateConjunto de dados
  1. v1
  2. 2 Fontes
  3. PUBLISHED
  1. v1
  2. 2 Fontes
  3. PUBLISHED

Ir para a pesquisa Baixar slides

ScholarGateComparar métodos: Factorial A/B Test · Full Factorial Experiment. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare