Vertaile menetelmiä

	Khiin neliövoima-analyysi	Tilastollisen voiman analyysi Pearsonin korrelaatiolle
Tieteenala	Tilastotiede	Tilastotiede
Menetelmäperhe	Hypothesis test	Hypothesis test
Syntyvuosi	1988	1988
Kehittäjä	Jacob Cohen	Jacob Cohen
Tyyppi	Sample size and power calculation	Sample size / power determination
Alkuperäislähde	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
Rinnakkaisnimet	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
Liittyvät	2	4
Tiivistelmä	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.