방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 요인 실험× | 분산 분석 (ANOVA)× | |
|---|---|---|
| 분야≠ | 실험설계 | 연구 통계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1926–1935 | 1925 |
| 창시자 | Ronald A. Fisher | Ronald A. Fisher |
| 유형≠ | Quantitative experimental design | Method |
| 원전≠ | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ | Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd. link ↗ |
| 별칭≠ | factorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design | ANOVA, F-test |
| 관련≠ | 6 | 4 |
| 요약≠ | A factorial experiment is an experimental design in which two or more independent variables (factors) are manipulated simultaneously, and every combination of their levels is tested. Introduced by Ronald Fisher in the 1920s–1930s, it is the standard approach whenever a researcher needs to detect not only the main effect of each factor but also whether the effect of one factor depends on the level of another — the interaction effect. | 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. |
| ScholarGate데이터셋 ↗ |
|
|