방법 비교

	다중 회귀분석을 위한 검정력 분석	Pearson 상관관계에 대한 통계적 검정력 분석
분야	통계학	통계학
계열	Hypothesis test	Hypothesis test
기원 연도	1988	1988
창시자	Jacob Cohen	Jacob Cohen
유형	A priori sample size determination	Sample size / power determination
원전	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
별칭	regression power analysis, sample size estimation regression, f² power analysis, Güç Analizi — Regresyon	Korelasyon Güç Analizi, power analysis for r, sample size for correlation
관련	4	4
요약	Power analysis for multiple regression is a pre-study procedure, formalised by Jacob Cohen (1988), that calculates the minimum sample size needed to detect a regression effect of a given size with adequate statistical power. It uses the anticipated R² (or the equivalent Cohen's f² effect size) and the number of predictors to determine how many observations must be collected before data collection begins.	Correlation power analysis is a pre-study calculation that determines how many participants are needed — or how much statistical power an existing sample provides — for a Pearson correlation test. Formalised by Jacob Cohen in his landmark 1988 text, it uses the expected correlation coefficient r directly as the effect size, so researchers can plan studies that are neither underpowered nor wastefully large.