Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Diseño Completamente Aleatorizado (CRD)× | Diseño Experimental Factorial Completo× | |
|---|---|---|
| Campo | Diseño experimental | Diseño experimental |
| Familia | Hypothesis test | Hypothesis test |
| Año de origen≠ | 1935 | 1926 |
| Autor original | R. A. Fisher | R. A. Fisher |
| Tipo≠ | Parametric group comparison via one-way ANOVA | Parametric factorial experiment |
| Fuente seminal≠ | 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 |
| Alias | 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) |
| Relacionados≠ | 3 | 5 |
| Resumen≠ | 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. |
| ScholarGateConjunto de datos ↗ |
|
|