방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 블록화된 완전 요인 설계 실험× | Full Factorial Experiment× | |
|---|---|---|
| 분야 | 실험설계 | 실험설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1935 (Fisher); systematized through 20th-century DOE literature | 1926 (Fisher's foundational paper); codified by the 1950s–1960s |
| 창시자≠ | R. A. Fisher (blocking principle); full factorial DOE tradition | Ronald A. Fisher |
| 유형 | Experimental design | Experimental design |
| 원전≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | 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 |
| 별칭 | blocked full factorial design, full factorial with blocking, complete factorial blocked design, BFF design | full factorial design, complete factorial design, 2^k factorial design, FFD |
| 관련≠ | 4 | 6 |
| 요약≠ | 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. | 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. |
| ScholarGate데이터셋 ↗ |
|
|