방법 비교

	베이즈 기술 통계	검정력 분석
분야	통계학	통계학
계열	Hypothesis test	Hypothesis test
기원 연도	1763/1812	1969 (1st ed.); 1988 (seminal 2nd ed.)
창시자	Thomas Bayes / Pierre-Simon Laplace	Jacob Cohen
유형	Bayesian parameter estimation	Sample size and power planning
원전	Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
별칭	Bayesian summaries, posterior descriptives, Bayesian parameter estimation, credible-interval summaries	sample size calculation, power calculation, sensitivity analysis, a priori power analysis
관련	5	5
요약	Bayesian descriptive statistics summarizes data by combining observed information with prior knowledge through Bayes' theorem, yielding posterior distributions over parameters such as the mean and variance. Instead of point estimates and p-values, results are expressed as posterior means, medians, and credible intervals that carry a direct probability interpretation.	Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (alpha), and statistical power (1 minus beta) — so that researchers can determine the sample size needed before data collection or evaluate the sensitivity of a completed study.