পদ্ধতির তুলনা করুন

	কাই-স্কোয়ার পাওয়ার অ্যানালাইসিস	পিয়ার্সন সহসম্বন্ধের জন্য পরিসংখ্যান শক্তি বিশ্লেষণ
ক্ষেত্র	পরিসংখ্যান	পরিসংখ্যান
পরিবার	Hypothesis test	Hypothesis test
উদ্ভবের বছর	1988	1988
প্রবর্তক	Jacob Cohen	Jacob Cohen
ধরন	Sample size and power calculation	Sample size / power determination
মৌলিক উৎস	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
অপর নাম	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
সম্পর্কিত	2	4
সারসংক্ষেপ	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.