Linganisha mbinu

	Uchanganuzi wa Nguvu wa Chi-Square	Uchambuzi wa Nguvu za Kimahesabu kwa Uhusiano wa Pearson
Nyanja	Takwimu	Takwimu
Familia	Hypothesis test	Hypothesis test
Mwaka wa asili	1988	1988
Mwanzilishi	Jacob Cohen	Jacob Cohen
Aina	Sample size and power calculation	Sample size / power determination
Chanzo asilia	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
Majina mbadala	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
Zinazohusiana	2	4
Muhtasari	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.