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| 2^(k-p) 分数析因设计× | 裂区实验设计× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 1961 | 1935 |
| 提出者≠ | George E. P. Box and J. Stuart Hunter | Frank Yates |
| 类型≠ | Screening and economical factorial design | Parametric mixed-model ANOVA |
| 开创性文献≠ | Box, G.E.P. & Hunter, J.S. (1961). The 2^(k-p) Fractional Factorial Designs. Technometrics, 3(3), 311–351. link ↗ | Yates, F. (1935). Complex Experiments. Supplement to the Journal of the Royal Statistical Society, 2(2), 181–247. DOI ↗ |
| 别名≠ | 2^k-p design, fractional factorial, screening design, Kesirli Faktöriyel Desen (2^k-p Fractional Factorial) | split-plot ANOVA, whole-plot sub-plot design, Bölünmüş Parsel Deseni (Split-Plot) |
| 相关≠ | 7 | 6 |
| 摘要≠ | The fractional factorial design is an economical experimental strategy that investigates k factors by running only a carefully chosen 1/2^p fraction of the full 2^k factorial experiment. Formalized by George E. P. Box and J. Stuart Hunter in their landmark 1961 Technometrics paper, it exploits the sparsity-of-effects principle — that high-order interactions are typically negligible — to screen many factors with far fewer runs than a complete factorial would require. | The split-plot design is a parametric experimental design that applies one factor to large whole plots and a second factor to subdivisions (sub-plots) within each whole plot. It was introduced by Frank Yates in 1935 to handle agricultural experiments where one factor — such as irrigation or tillage method — is difficult or impractical to change frequently, while a second factor can be varied more easily within the same plot. |
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