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| Thử nghiệm A/B theo yếu tố× | Thí nghiệm yếu tố× | |
|---|---|---|
| Lĩnh vực | Thiết kế thí nghiệm | Thiết kế thí nghiệm |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | Factorial design: 1920s–1930s; applied online as factorial A/B test: 2000s–2010s | 1926–1935 |
| Người khởi xướng≠ | Ronald A. Fisher (factorial design); digital A/B testing popularized by Google, Microsoft, and Amazon in the 2000s | Ronald A. Fisher |
| Loại≠ | Controlled online/field experiment | Quantitative experimental design |
| Công trình gốc≠ | Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press. ISBN: 978-1108724265 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Tên gọi khác | factorial split test, multi-factor A/B test, factorial online experiment, factorial controlled experiment | factorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design |
| Liên quan | 6 | 6 |
| Tóm tắt≠ | A 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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