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| Shapiro-Wilk 정규성 검정× | 독립 표본 t-검정× | 일원 분산 분석× | |
|---|---|---|---|
| 분야 | 통계학 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1965 | 1908 | 1925 |
| 창시자≠ | S. S. Shapiro & M. B. Wilk | Student (W. S. Gosset) | Ronald A. Fisher |
| 유형≠ | Normality (goodness-of-fit) test | Parametric mean comparison | Parametric mean comparison |
| 원전≠ | Shapiro, S. S. & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4), 591–611. DOI ↗ | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| 별칭≠ | Shapiro-Wilk W test, W test for normality, Shapiro-Wilk normallik testi | student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| 관련≠ | 2 | 4 | 4 |
| 요약≠ | 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. | The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances. | One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925. |
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