方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 分数析因实验× | 全因子实验× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1945 (Finney); broader development 1950s–1970s by Box, Hunter | 1926 (Fisher's foundational paper); codified by the 1950s–1960s |
| 提出者≠ | D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work | Ronald A. Fisher |
| 类型≠ | Quantitative experimental design | Experimental design |
| 开创性文献 | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130 | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130 |
| 别名 | fractional factorial design, FFD, 2^(k-p) design, fractional replication | full factorial design, complete factorial design, 2^k factorial design, FFD |
| 相关≠ | 4 | 6 |
| 摘要≠ | A fractional factorial experiment is a resource-efficient experimental design that tests only a carefully chosen fraction of all possible factor-level combinations. By exploiting the principle that high-order interactions are usually negligible, it identifies the main effects and low-order interactions of k factors using far fewer runs than a full factorial design — making it the workhorse of industrial and engineering screening experiments. | A full factorial experiment runs every possible combination of all chosen factor levels, making it the gold standard for simultaneously estimating main effects, two-way interactions, and higher-order interactions among multiple independent variables. Introduced through Ronald Fisher's foundational work on factorial designs in the 1920s and systematised by Box, Hunter, and Montgomery, it provides complete information about how factors act individually and in combination on an outcome. |
| ScholarGate数据集 ↗ |
|
|