Сравнение методов

	Критерий нормальности Шапиро-Уилка	Независимый t-критерий для двух выборок	Однофакторный дисперсионный анализ
Область	Статистика	Статистика	Статистика
Семейство	Hypothesis test	Hypothesis test	Hypothesis test
Год появления	1965	1908	1925
Автор метода	S. S. Shapiro & M. B. Wilk	Student (W. S. Gosset)	Ronald A. Fisher
Тип	Normality (goodness-of-fit) test	Parametric mean comparison	Parametric mean comparison
Основополагающий источник	Shapiro, S. S. & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4), 591–611.	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.
Другие названия	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
Связанные	2	4	4
Сводка	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.