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。
| 全因子实验× | 区组完全析因实验× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1926 (Fisher's foundational paper); codified by the 1950s–1960s | 1935 (Fisher); systematized through 20th-century DOE literature |
| 提出者≠ | Ronald A. Fisher | R. A. Fisher (blocking principle); full factorial DOE tradition |
| 类型 | 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 | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 |
| 别名 | full factorial design, complete factorial design, 2^k factorial design, FFD | blocked full factorial design, full factorial with blocking, complete factorial blocked design, BFF design |
| 相关≠ | 6 | 4 |
| 摘要≠ | 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. | A blocked full factorial experiment tests every combination of all factor levels while grouping experimental runs into homogeneous blocks to isolate a known nuisance variable. This design preserves the power to detect all main effects and interactions of the factors of interest while preventing batch-to-batch, day-to-day, or machine-to-machine variability from inflating experimental error. |
| ScholarGate数据集 ↗ |
|
|