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Test A/B Pragmatic×Disegno sperimentale fattoriale completo×
CampoDisegno sperimentaleDisegno sperimentale
FamigliaProcess / pipelineHypothesis test
Anno di origine1967 (pragmatic framing); 2007–2012 (large-scale tech A/B testing practice)1926
IdeatorePragmatic trial framing: Schwartz & Lellouch (1967); A/B testing in technology: Ron Kohavi and colleagues at Microsoft (~2007–2012)R. A. Fisher
TipoRandomized comparative experimentParametric factorial experiment
Fonte seminaleSchwartz, D., & Lellouch, J. (1967). Explanatory and pragmatic attitudes in therapeutical trials. Journal of Chronic Diseases, 20(8), 637–648. DOI ↗Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130
Aliaspragmatic split test, real-world A/B experiment, pragmatic online experiment, pragmatic controlled experimentfactorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k)
Correlati35
SintesiA pragmatic A/B test is a randomized comparative experiment that evaluates two alternatives — a control (A) and a treatment (B) — under real-world operating conditions rather than tightly controlled laboratory settings. Rooted in the pragmatic-versus-explanatory trial distinction introduced by Schwartz and Lellouch in 1967 and brought to large-scale practice by online experimentation teams at Microsoft, Google, and Amazon, it prioritizes decision-relevant effectiveness over internal mechanistic explanation.A full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured.
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ScholarGateConfronta i metodi: Pragmatic A/B Test · Full Factorial Design. Consultato il 2026-06-18 da https://scholargate.app/it/compare