Σύγκριση μεθόδων

	Δοκιμή A/B (Διαδικτυακό Ελεγχόμενο Πείραμα)	Σχεδιασμός διαδοχικών / ομαδικών διαδοχικών δοκιμών
Πεδίο	Πειραματικός Σχεδιασμός	Πειραματικός Σχεδιασμός
Οικογένεια	Hypothesis test	Hypothesis test
Έτος προέλευσης	1935	1979
Δημιουργός	Ron Kohavi et al. (Microsoft); conceptual roots in R. A. Fisher's randomized experiments (1935)	O'Brien & Fleming; Pocock; Lan & DeMets
Τύπος	Parametric comparison (frequentist or Bayesian)	Adaptive stopping trial design
Θεμελιώδης πηγή	Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press. ISBN: 9781108724265	O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556.
Εναλλακτικές ονομασίες	split test, controlled experiment, two-variant test, A/B Testi (Online Kontrollü Deney)	group sequential design, adaptive stopping design, Ardışık Deneme Tasarımı (Sequential / Group Sequential)
Συναφείς	4	3
Σύνοψη	An A/B test is a randomized controlled experiment that simultaneously exposes two groups of users to a control variant (A) and a treatment variant (B) in order to determine whether a measured outcome differs significantly between them. The modern online controlled experiment framework was systematized by Ron Kohavi and colleagues at Microsoft in the early 2000s, building on R. A. Fisher's classical randomization principles from 1935. It is the dominant causal inference tool in web product development, digital marketing, and experimentation platforms.	Sequential and group sequential trial designs allow a study to be stopped early — or continued — based on interim analyses conducted as data accumulate. The core framework was formalised by O'Brien and Fleming in 1979 and extended by Lan and DeMets's alpha-spending approach, and it controls the overall Type I error rate across all planned looks by pre-specifying both efficacy and futility boundaries before enrolment begins.