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| Test d'Anderson-Darling de normalitat× | Test de Kolmogorov-Smirnov per a dues mostres× | |
|---|---|---|
| Camp | Estadística | Estadística |
| Família | Regression model | Regression model |
| Any d'origen≠ | 1952 | 1948 |
| Autor original≠ | Anderson & Darling (1952); EDF tables by Stephens (1974) | N. V. Smirnov |
| Tipus≠ | Empirical distribution function (EDF) goodness-of-fit test | Nonparametric two-sample distribution test |
| Font seminal≠ | 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 ↗ | Smirnov, N. V. (1948). Table for Estimating the Goodness of Fit of Empirical Distributions. Annals of Mathematical Statistics, 19(2), 279-281. DOI ↗ |
| Àlies≠ | Anderson-Darling Normallik Testi, A-squared test, AD test, Anderson-Darling goodness-of-fit test | KS two-sample test, two-sample KS test, İki Örneklem Kolmogorov-Smirnov Testi |
| Relacionats≠ | 5 | 3 |
| Resum≠ | 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 two-sample Kolmogorov-Smirnov test is a nonparametric procedure that asks whether two independent groups are drawn from the same continuous distribution. Building on Smirnov's 1948 tables, it compares the empirical cumulative distribution functions (CDFs) of the two samples and uses their maximum absolute distance as the test statistic. |
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