Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Schéma en carré latin et en carré gréco-latin× | Schéma expérimental en parcelles divisées× | |
|---|---|---|
| Domaine | Plans d'expériences | Plans d'expériences |
| Famille | Hypothesis test | Hypothesis test |
| Année d'origine | 1935 | 1935 |
| Auteur d'origine≠ | Ronald A. Fisher | Frank Yates |
| Type≠ | Parametric blocked ANOVA | Parametric mixed-model ANOVA |
| Source fondatrice≠ | 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 ↗ |
| Alias | 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) |
| Apparentées≠ | 5 | 6 |
| Résumé≠ | 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. |
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