विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| पायलट प्रभाजी गुणनखंड प्रयोग (Pilot Fractional Factorial Experiment)× | आंशिक गुणनखंड प्रयोग× | |
|---|---|---|
| क्षेत्र | प्रयोगात्मक अभिकल्प | प्रयोगात्मक अभिकल्प |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1950s–1960s (fractional factorial foundation); pilot study integration formalized in 20th century DOE practice | 1945 (Finney); broader development 1950s–1970s by Box, Hunter |
| प्रवर्तक≠ | Box, Hunter & Hunter (fractional factorial); pilot study concept developed broadly in industrial and clinical experimentation | D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work |
| प्रकार≠ | Experimental screening design (pilot phase) | Quantitative experimental design |
| मौलिक स्रोत≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443 | 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 |
| उपनाम | pilot FFE, screening pilot design, pilot fractional factorial, pilot FF screening study | fractional factorial design, FFD, 2^(k-p) design, fractional replication |
| संबंधित≠ | 5 | 4 |
| सारांश≠ | A pilot fractional factorial experiment is a small-scale preliminary study that uses a fractional factorial design — testing only a subset of all possible factor combinations — to screen multiple factors simultaneously before committing to a full-scale investigation. It provides early estimates of effect sizes, variance, and feasibility at substantially reduced cost and participant burden compared to a full factorial pilot or a full-scale trial. | 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. |
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