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| Pilot Fuldt Faktorialt Eksperiment× | Fuld Faktoriel Eksperiment× | |
|---|---|---|
| Fagområde | Forsøgsdesign | Forsøgsdesign |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | 1920s (Fisher); pilot usage formalised mid-20th century | 1926 (Fisher's foundational paper); codified by the 1950s–1960s |
| Ophavsperson≠ | R. A. Fisher (full factorial foundations); pilot application codified in applied DOE literature (Box, Hunter & Hunter; Montgomery) | Ronald A. Fisher |
| Type≠ | Experimental design (pilot/screening phase) | Experimental design |
| Oprindelig kilde≠ | 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 |
| Aliasser | pilot factorial design, pilot 2^k design, pilot complete factorial experiment, screening factorial pilot | full factorial design, complete factorial design, 2^k factorial design, FFD |
| Relaterede≠ | 3 | 6 |
| Resumé≠ | A pilot full factorial experiment is a small-scale, complete crossing of all selected factors at all their levels, run before a definitive study to gather preliminary effect estimates, assess variability, and verify experimental logistics. It retains the complete combinatorial structure of a full factorial design — every combination of factor levels is tested — but is intentionally limited in scope (fewer replicates, narrower factor ranges) to conserve resources while maximising learning about factor effects and interactions before committing to a larger investigation. | 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. |
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