ScholarGate
Asistent

Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Analýza kovariance (ANCOVA)×Diskriminační analýza×Nezávislý t-test×
OborStatistikaStatistikaStatistika
RodinaHypothesis testLatent structureHypothesis test
Rok vzniku193219361908
TvůrceRonald A. FisherRonald A. FisherStudent (W. S. Gosset)
TypParametric group comparison with covariate controlSupervised classification and dimension reductionParametric mean comparison
Původní zdrojTabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574Fisher, 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 ↗
Další názvyanalysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysisstudent t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
Příbuzné444
ShrnutíANCOVA is a parametric hypothesis test that compares the adjusted means of two or more independent groups while statistically controlling for one or more continuous covariates. By removing the portion of outcome variance explained by the covariate, ANCOVA increases statistical precision and produces fairer group comparisons. The method builds on the general linear model framework consolidated by Fisher in the early 1930s and is described comprehensively by Tabachnick and Fidell (2013).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.
ScholarGateDatová sada
  1. v1
  2. 1 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v2
  2. 2 Zdroje
  3. PUBLISHED

Přejít na hledání Stáhnout prezentaci

ScholarGatePorovnat metody: ANCOVA · Discriminant Analysis · Independent t-test. Získáno 2026-06-20 z https://scholargate.app/cs/compare