Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Повністю випадковий дизайн (CRD)× | Повнофакторний експериментальний план× | Однофакторний дисперсійний аналіз× | |
|---|---|---|---|
| Галузь≠ | Планування експерименту | Планування експерименту | Статистика |
| Родина | Hypothesis test | Hypothesis test | Hypothesis test |
| Рік появи≠ | 1935 | 1926 | 1925 |
| Автор методу≠ | R. A. Fisher | R. A. Fisher | Ronald A. Fisher |
| Тип≠ | Parametric group comparison via one-way ANOVA | Parametric factorial experiment | Parametric mean comparison |
| Основоположне джерело≠ | Montgomery, D.C. (2017). Design and Analysis of Experiments. Wiley. ISBN: 978-1119320937 | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130 | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| Інші назви | CRD, completely randomised design, one-way experimental design, Tam Tesadüf Deneme Deseni (CRD) | factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k) | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| Пов'язані≠ | 3 | 5 | 4 |
| Підсумок≠ | The completely randomized design is the most fundamental experimental design, in which experimental units are assigned to treatments entirely at random with no restrictions. Analysed by one-way ANOVA, it was formalised by R. A. Fisher in the 1930s and remains the reference starting point for experimental research whenever the experimental material is homogeneous and nuisance variation is absent or negligible. | A full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured. | One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925. |
| ScholarGateНабір даних ↗ |
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