השוואת שיטות

	ניתוח עוצמה סטטיסטי למקדם המתאם של פירסון	ניתוח עוצמה עבור ANOVA
תחום	סטטיסטיקה	סטטיסטיקה
משפחה	Hypothesis test	Hypothesis test
שנת המקור	1988	1988
הוגה השיטה	Jacob Cohen	Jacob Cohen
סוג	Sample size / power determination	Sample size determination
מקור מכונן	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
כינויים	Korelasyon Güç Analizi, power analysis for r, sample size for correlation	ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA
קשורות	4	4
תקציר	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.	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.