方法对比
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| 判别分析× | 独立样本t检验× | 单因素方差分析× | |
|---|---|---|---|
| 领域 | 统计学 | 统计学 | 统计学 |
| 方法族≠ | Latent structure | Hypothesis test | Hypothesis test |
| 起源年份≠ | 1936 | 1908 | 1925 |
| 提出者≠ | Ronald A. Fisher | Student (W. S. Gosset) | Ronald A. Fisher |
| 类型≠ | Supervised classification and dimension reduction | Parametric mean comparison | Parametric mean comparison |
| 开创性文献≠ | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. 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 ↗ |
| 别名 | 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 |
| 相关 | 4 | 4 | 4 |
| 摘要≠ | 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. |
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