Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Deseas eksperimentālā dizaina shēma× | Divu faktoru dispersijas analīze (Divu faktoru ANOVA)× | |
|---|---|---|
| Nozare≠ | Eksperimentu plānošana | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1935 | 1925 |
| Autors≠ | Frank Yates | Ronald A. Fisher |
| Tips≠ | Parametric mixed-model ANOVA | Parametric factorial mean comparison |
| Pirmavots≠ | Yates, F. (1935). Complex Experiments. Supplement to the Journal of the Royal Statistical Society, 2(2), 181–247. DOI ↗ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 |
| Citi nosaukumi | split-plot ANOVA, whole-plot sub-plot design, Bölünmüş Parsel Deseni (Split-Plot) | factorial ANOVA, two-factor ANOVA, İki Yönlü ANOVA |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | 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. | Two-Way ANOVA is a parametric hypothesis test that simultaneously examines the main effects of two independent categorical factors and their interaction effect on a single continuous dependent variable. The technique was developed within the broader framework of the analysis of variance established by Ronald A. Fisher in 1925 and remains the standard approach whenever an experiment or survey includes exactly two between-subjects factors. |
| ScholarGateDatu kopa ↗ |
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