Módszerek összehasonlítása

	Statisztikai teljesítményelemzés Pearson-korrelációhoz	Teljesítményanalízis ANOVA-hoz
Tudományterület	Statisztika	Statisztika
Módszercsalád	Hypothesis test	Hypothesis test
Keletkezés éve	1988	1988
Megalkotó	Jacob Cohen	Jacob Cohen
Típus	Sample size / power determination	Sample size determination
Alapmű	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
Alternatív nevek	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
Kapcsolódó	4	4
Összefoglaló	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.