手法を比較

	A/Bテスト（オンライン制御実験）	独立標本t検定
分野	実験計画法	統計学
系統	Hypothesis test	Hypothesis test
提唱年	1935	1908
提唱者	Ron Kohavi et al. (Microsoft); conceptual roots in R. A. Fisher's randomized experiments (1935)	Student (W. S. Gosset)
種類	Parametric comparison (frequentist or Bayesian)	Parametric mean comparison
原典	Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press. ISBN: 9781108724265	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.
別名	split test, controlled experiment, two-variant test, A/B Testi (Online Kontrollü Deney)	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
関連	4	4
概要	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.	The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances.