Сравнение методов

	Дискриминантный анализ	Независимый t-критерий для двух выборок	Однофакторный дисперсионный анализ
Область	Статистика	Статистика	Статистика
Семейство	Latent structure	Hypothesis test	Hypothesis test
Год появления	1936	1908	1925
Автор метода	Ronald A. Fisher	Student (W. S. Gosset)	Ronald A. Fisher
Тип	Supervised classification and dimension reduction	Parametric mean comparison	Parametric mean comparison
Основополагающий источник	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.	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	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis	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	4	4	4
Сводка	Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error.	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.