Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Пилотный факторный эксперимент× | Методология поверхности отклика (RSM)× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство≠ | Process / pipeline | Hypothesis test |
| Год появления≠ | 1930s (Fisher); pilot application conventions developed mid-20th century | 1951 |
| Автор метода≠ | R. A. Fisher (factorial design foundations); formalized in experimental statistics literature | George E. P. Box & K. B. Wilson |
| Тип≠ | Preliminary experimental design | Second-order polynomial response surface model |
| Основополагающий источник≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | Box, G. E. P. & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society, Series B, 13(1), 1–45. link ↗ |
| Другие названия≠ | preliminary factorial study, pilot factorial design, small-scale factorial trial, feasibility factorial experiment | RSM, Central Composite Design, Box-Behnken Design, CCD |
| Связанные≠ | 2 | 7 |
| Сводка≠ | A pilot factorial experiment is a small-scale, preliminary study that employs a factorial structure to simultaneously vary two or more factors across a limited number of experimental units. Its purpose is not to deliver definitive conclusions but to estimate effect sizes, within-group variance, and factor interactions, and to test logistical feasibility before committing resources to a full-scale factorial experiment. It is widely used in behavioral sciences, engineering, agriculture, and clinical research as an essential planning step. | Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics. |
| ScholarGateНабор данных ↗ |
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