পদ্ধতির তুলনা করুন

	পিয়ার্সন সহসম্বন্ধের জন্য পরিসংখ্যান শক্তি বিশ্লেষণ	পিয়ারসন গুণফল-মুহূর্ত সহসম্বন্ধ গুণাঙ্ক
ক্ষেত্র	পরিসংখ্যান	পরিসংখ্যান
পরিবার	Hypothesis test	Hypothesis test
উদ্ভবের বছর	1988	1895
প্রবর্তক	Jacob Cohen	Karl Pearson
ধরন	Sample size / power determination	Parametric correlation
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.
অপর নাম	Korelasyon Güç Analizi, power analysis for r, sample size for correlation	pearson r, product-moment correlation, bivariate correlation, Pearson Korelasyon Analizi
সম্পর্কিত	4	4
সারসংক্ষেপ	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.	The Pearson product-moment correlation coefficient (r) is a parametric measure of the direction and strength of the linear association between two continuous variables. Introduced by Karl Pearson in 1895, it remains the most widely used bivariate correlation statistic in the social, health, and natural sciences. The coefficient ranges from −1 (perfect negative linear relationship) to +1 (perfect positive), with 0 indicating no linear association.