विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| Single-blind Full Factorial Experiment× | आंशिक गुणनखंड प्रयोग× | |
|---|---|---|
| क्षेत्र | प्रयोगात्मक अभिकल्प | प्रयोगात्मक अभिकल्प |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | Full factorial: 1935 (Fisher); single-blind clinical convention: mid-20th century | 1945 (Finney); broader development 1950s–1970s by Box, Hunter |
| प्रवर्तक≠ | Full factorial framework: R. A. Fisher; single-blind masking practice: clinical trial tradition, standardized by the 20th century | D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work |
| प्रकार≠ | Controlled experimental design | Quantitative experimental design |
| मौलिक स्रोत≠ | 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 |
| उपनाम | single-masked full factorial, single-blind complete factorial, SB-FFE, single-blind all-combinations design | fractional factorial design, FFD, 2^(k-p) design, fractional replication |
| संबंधित≠ | 6 | 4 |
| सारांश≠ | A single-blind full factorial experiment systematically tests every combination of all factor levels while keeping participants unaware of their treatment assignment. This design allows simultaneous estimation of all main effects and all interaction effects between factors, with single-blind masking reducing participant-side biases such as demand characteristics and expectation effects — without requiring investigator blinding. | 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. |
| ScholarGateडेटासेट ↗ |
|
|