方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| Anderson-Darling正态性检验× | 夏皮罗-威尔克正态性检验× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族≠ | Regression model | Hypothesis test |
| 起源年份≠ | 1952 | 1965 |
| 提出者≠ | Anderson & Darling (1952); EDF tables by Stephens (1974) | S. S. Shapiro & M. B. Wilk |
| 类型≠ | Empirical distribution function (EDF) goodness-of-fit test | Normality (goodness-of-fit) test |
| 开创性文献≠ | Anderson, T. W., & Darling, D. A. (1952). Asymptotic Theory of Certain 'Goodness of Fit' Criteria Based on Stochastic Processes. The Annals of Mathematical Statistics, 23(2), 193-212. DOI ↗ | Shapiro, S. S. & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4), 591–611. DOI ↗ |
| 别名≠ | Anderson-Darling Normallik Testi, A-squared test, AD test, Anderson-Darling goodness-of-fit test | Shapiro-Wilk W test, W test for normality, Shapiro-Wilk normallik testi |
| 相关≠ | 5 | 2 |
| 摘要≠ | The Anderson-Darling test is an empirical distribution function (EDF) goodness-of-fit test, introduced by Anderson and Darling in 1952, that checks whether a continuous sample comes from a specified distribution such as the normal, exponential, or Weibull. By weighting deviations more heavily in the tails, it detects departures in the distribution's extremes more powerfully than the Kolmogorov-Smirnov test. | The Shapiro-Wilk test is a hypothesis test that checks whether a continuous variable was drawn from a normal distribution. It was introduced by Samuel Shapiro and Martin Wilk in 1965 and is regarded as one of the most powerful normality tests, recommended for sample sizes below 5000. |
| ScholarGate数据集 ↗ |
|
|