方法对比
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| 贝叶斯描述性统计× | 功效分析× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 1763/1812 | 1969 (1st ed.); 1988 (seminal 2nd ed.) |
| 提出者≠ | Thomas Bayes / Pierre-Simon Laplace | Jacob Cohen |
| 类型≠ | Bayesian parameter estimation | Sample size and power planning |
| 开创性文献≠ | 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 |
| 别名 | Bayesian summaries, posterior descriptives, Bayesian parameter estimation, credible-interval summaries | sample size calculation, power calculation, sensitivity analysis, a priori power analysis |
| 相关 | 5 | 5 |
| 摘要≠ | 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. |
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