เปรียบเทียบวิธี

	การวิเคราะห์ความแปรปรวนร่วม (Multivariate Analysis of Variance - MANOVA)	การวิเคราะห์จำแนก (Discriminant Analysis)	การทดสอบทีสำหรับตัวอย่างอิสระ	การวิเคราะห์ความแปรปรวนทางเดียว
สาขาวิชา	สถิติศาสตร์	สถิติศาสตร์	สถิติศาสตร์	สถิติศาสตร์
ตระกูล	Hypothesis test	Latent structure	Hypothesis test	Hypothesis test
ปีกำเนิด	1932	1936	1908	1925
ผู้ริเริ่ม	Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)	Ronald A. Fisher	Student (W. S. Gosset)	Ronald A. Fisher
ประเภท	Parametric multivariate mean comparison	Supervised classification and dimension reduction	Parametric mean comparison	Parametric mean comparison
แหล่งต้นตำรับ	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.	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.
ชื่อเรียกอื่น	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	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
ที่เกี่ยวข้อง	5	4	4	4
สรุป	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.	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.