Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Факторный лабораторный эксперимент× | Дисперсионный анализ (ANOVA)× | |
|---|---|---|
| Область≠ | Планирование эксперимента | Статистика исследований |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1926 (Fisher's factorial principle); laboratory application systematized mid-20th century | 1925 |
| Автор метода | Ronald A. Fisher | Ronald A. Fisher |
| Тип≠ | Experimental research design | Method |
| Основополагающий источник≠ | Kirk, R. E. (2013). Experimental Design: Procedures for the Behavioral Sciences (4th ed.). Sage Publications. ISBN: 978-1412974455 | Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd. link ↗ |
| Другие названия≠ | factorial lab experiment, laboratory factorial design, factorial controlled experiment, multi-factor lab study | ANOVA, F-test |
| Связанные≠ | 2 | 4 |
| Сводка≠ | A factorial laboratory experiment is a controlled experimental design in which two or more independent variables (factors) are simultaneously manipulated, each at two or more levels, within a laboratory setting. This design allows researchers to estimate both the individual main effect of each factor and the interaction effects between factors — making it one of the most efficient and informative designs in behavioral, psychological, and natural science research. | ANOVA is a parametric statistical method developed by Ronald A. Fisher in 1925 that tests whether means differ significantly across three or more independent groups. By partitioning total variance into between-group and within-group components, ANOVA determines whether observed differences are likely due to treatment effects or random variation, making it fundamental to comparative research across medicine, psychology, agriculture, and engineering. |
| ScholarGateНабор данных ↗ |
|
|