Порівняння методів

	Аналіз потужності хі-квадрат	Аналіз потужності для дисперсійного аналізу
Галузь	Статистика	Статистика
Родина	Hypothesis test	Hypothesis test
Рік появи	1988	1988
Автор методу	Jacob Cohen	Jacob Cohen
Тип	Sample size and power calculation	Sample size determination
Основоположне джерело	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
Інші назви	chi-square power, chi-square sample size, Ki-Kare Güç Analizi, goodness-of-fit power	ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA
Пов'язані	2	4
Підсумок	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.	Power analysis for ANOVA is a prospective statistical technique that determines the minimum sample size needed to detect a specified group mean difference with a chosen probability. Formalized by Jacob Cohen in his 1988 monograph, it translates a researcher's effect size expectation — expressed as Cohen's f — along with the desired Type I error rate (alpha) and statistical power (1 − beta) into a concrete per-group sample size recommendation for one-way or factorial ANOVA designs.