方法对比
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| 贝叶斯单样本t检验× | 单样本t检验× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 2009 | 1908 |
| 提出者≠ | Rouder, Speckman, Sun, Morey & Iverson | Student (W. S. Gosset) |
| 类型≠ | Bayesian mean-vs-constant comparison | Parametric mean comparison |
| 开创性文献≠ | Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16(2), 225–237. DOI ↗ | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ |
| 别名 | Bayesian single-sample t-test, Bayes factor one-sample t-test, JZS one-sample Bayes factor, Bayesian location test | single-sample t-test, one-group t-test, one-sample t, Student one-sample t-test |
| 相关≠ | 2 | 3 |
| 摘要≠ | The Bayesian one-sample t-test compares a single group's mean against a fixed reference value using a Bayes factor rather than a p-value. It quantifies the evidence the data provide for the null hypothesis (mean equals the reference) versus the alternative, and yields a full posterior distribution over the effect size — enabling statements about practical magnitude, not just a binary reject-or-retain decision. | The one-sample t-test is a parametric hypothesis test that determines whether the mean of a single sample differs significantly from a known or hypothesized population value. Derived from Student's (Gosset's) 1908 t-distribution, it assumes continuous, approximately normally distributed data and is one of the most fundamental tests in applied statistics. |
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