방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 요인 실험실 실험× | 분산 분석 (ANOVA)× | |
|---|---|---|
| 분야≠ | 실험설계 | 연구 통계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1926 (Fisher's factorial principle); laboratory application systematized mid-20th century | 1925 |
| 창시자 | Ronald A. Fisher | Ronald A. Fisher |
| 유형≠ | Experimental research design | Method |
| 원전≠ | 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 ↗ |
| 별칭≠ | factorial lab experiment, laboratory factorial design, factorial controlled experiment, multi-factor lab study | ANOVA, F-test |
| 관련≠ | 2 | 4 |
| 요약≠ | 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. |
| ScholarGate데이터셋 ↗ |
|
|