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| Test Kołmogorowa-Smirnowa dla normalności× | Test normalności Shapiro-Wilka× | |
|---|---|---|
| Dziedzina | Statystyka | Statystyka |
| Rodzina≠ | Regression model | Hypothesis test |
| Rok powstania≠ | 1967 | 1965 |
| Twórca≠ | Hubert W. Lilliefors | S. S. Shapiro & M. B. Wilk |
| Typ≠ | Goodness-of-fit / normality test | Normality (goodness-of-fit) test |
| Źródło pierwotne≠ | 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 ↗ | Shapiro, S. S. & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4), 591–611. DOI ↗ |
| Inne nazwy | Lilliefors corrected Kolmogorov-Smirnov test, Lilliefors normality test, Lilliefors Testi | Shapiro-Wilk W test, W test for normality, Shapiro-Wilk normallik testi |
| Pokrewne≠ | 5 | 2 |
| Podsumowanie≠ | 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. | 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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