השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח שונות רב-משתני (MANOVA)× | ניתוח מבחין× | מבחן t למדגמים בלתי תלויים× | |
|---|---|---|---|
| תחום | סטטיסטיקה | סטטיסטיקה | סטטיסטיקה |
| משפחה≠ | Hypothesis test | Latent structure | Hypothesis test |
| שנת המקור≠ | 1932 | 1936 | 1908 |
| הוגה השיטה≠ | Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.) | Ronald A. Fisher | Student (W. S. Gosset) |
| סוג≠ | Parametric multivariate mean comparison | Supervised classification and dimension reduction | Parametric mean comparison |
| מקור מכונן≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | 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 ↗ |
| כינויים≠ | Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA) | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis | student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi |
| קשורות≠ | 5 | 4 | 4 |
| תקציר≠ | MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932. | 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. |
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