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| Test di normalità di Anderson-Darling× | Test di normalità di Shapiro-Wilk× | |
|---|---|---|
| Campo | Statistica | Statistica |
| Famiglia≠ | Regression model | Hypothesis test |
| Anno di origine≠ | 1952 | 1965 |
| Ideatore≠ | Anderson & Darling (1952); EDF tables by Stephens (1974) | S. S. Shapiro & M. B. Wilk |
| Tipo≠ | Empirical distribution function (EDF) goodness-of-fit test | Normality (goodness-of-fit) test |
| Fonte seminale≠ | 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 ↗ |
| Alias≠ | 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 |
| Correlati≠ | 5 | 2 |
| Sintesi≠ | 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. |
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