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	Chi-kvadrat-effektanalys	Statistisk styrkeanalys för Pearsons korrelation
Ämnesområde	Statistik	Statistik
Familj	Hypothesis test	Hypothesis test
Ursprungsår	1988	1988
Upphovsperson	Jacob Cohen	Jacob Cohen
Typ	Sample size and power calculation	Sample size / power determination
Ursprungskälla	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
Alias	chi-square power, chi-square sample size, Ki-Kare Güç Analizi, goodness-of-fit power	Korelasyon Güç Analizi, power analysis for r, sample size for correlation
Närliggande	2	4
Sammanfattning	Chi-square power analysis is a prospective calculation that determines the minimum sample size required — or the statistical power achievable with a given sample — for chi-square independence tests or goodness-of-fit tests. It rests on Cohen's w effect size framework, codified by Jacob Cohen in his landmark 1988 work on statistical power for the behavioral sciences.	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.