Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Дизайн Латинского квадрата и Греко-Латинского квадрата× | Экспериментальный план с расщеплёнными делянками× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Hypothesis test | Hypothesis test |
| Год появления | 1935 | 1935 |
| Автор метода≠ | Ronald A. Fisher | Frank Yates |
| Тип≠ | Parametric blocked ANOVA | Parametric mixed-model ANOVA |
| Основополагающий источник≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443 | Yates, F. (1935). Complex Experiments. Supplement to the Journal of the Royal Statistical Society, 2(2), 181–247. DOI ↗ |
| Другие названия | Latin Square, Greco-Latin Square, Latin Kare ve Greco-Latin Kare Deseni | split-plot ANOVA, whole-plot sub-plot design, Bölünmüş Parsel Deseni (Split-Plot) |
| Связанные≠ | 5 | 6 |
| Сводка≠ | The Latin square design is a blocked experimental design that simultaneously controls two independent nuisance factors — the row block and the column block — so that each treatment appears exactly once in every row and every column of an n×n arrangement. Formalised by Ronald A. Fisher in his 1935 monograph The Design of Experiments, the design dramatically reduces experimental error by absorbing variation from two extraneous sources before the treatment effects are estimated. | The split-plot design is a parametric experimental design that applies one factor to large whole plots and a second factor to subdivisions (sub-plots) within each whole plot. It was introduced by Frank Yates in 1935 to handle agricultural experiments where one factor — such as irrigation or tillage method — is difficult or impractical to change frequently, while a second factor can be varied more easily within the same plot. |
| ScholarGateНабор данных ↗ |
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