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| Uji Normalitas Anderson-Darling× | Uji Lilliefors untuk Normalitas× | |
|---|---|---|
| Bidang | Statistika | Statistika |
| Keluarga | Regression model | Regression model |
| Tahun asal≠ | 1952 | 1967 |
| Pencetus≠ | Anderson & Darling (1952); EDF tables by Stephens (1974) | Hubert W. Lilliefors |
| Tipe≠ | Empirical distribution function (EDF) goodness-of-fit test | Goodness-of-fit / normality test |
| Sumber perintis≠ | 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 ↗ | Lilliefors, H. W. (1967). On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown. Journal of the American Statistical Association, 62(318), 399-402. DOI ↗ |
| Alias≠ | Anderson-Darling Normallik Testi, A-squared test, AD test, Anderson-Darling goodness-of-fit test | Lilliefors corrected Kolmogorov-Smirnov test, Lilliefors normality test, Lilliefors Testi |
| Terkait | 5 | 5 |
| Ringkasan≠ | 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 Lilliefors test is a goodness-of-fit test that checks whether a continuous sample comes from a normal (or exponential) distribution when the mean and variance are unknown and estimated from the data. Introduced by Hubert W. Lilliefors in 1967, it adjusts the critical values of the Kolmogorov-Smirnov test so that they remain valid once the distribution's parameters are estimated rather than known in advance. |
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