Comparar métodos

	Análise de Poder Estatístico para Correlação de Pearson	Análise de Potência para ANOVA
Área	Estatística	Estatística
Família	Hypothesis test	Hypothesis test
Ano de origem	1988	1988
Autor original	Jacob Cohen	Jacob Cohen
Tipo	Sample size / power determination	Sample size determination
Fonte seminal	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
Outros nomes	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
Relacionados	4	4
Resumo	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.