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| ANOVA를 위한 검정력 분석× | 일원 분산 분석× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1988 | 1925 |
| 창시자≠ | Jacob Cohen | Ronald A. Fisher |
| 유형≠ | Sample size determination | Parametric mean comparison |
| 원전≠ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| 별칭 | ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| 관련 | 4 | 4 |
| 요약≠ | Power analysis for ANOVA is a prospective statistical technique that determines the minimum sample size needed to detect a specified group mean difference with a chosen probability. Formalized by Jacob Cohen in his 1988 monograph, it translates a researcher's effect size expectation — expressed as Cohen's f — along with the desired Type I error rate (alpha) and statistical power (1 − beta) into a concrete per-group sample size recommendation for one-way or factorial ANOVA designs. | 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. |
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