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Ανάλυση Μεγέθους Επίδρασης×t-test ανεξαρτήτων δειγμάτων×
ΠεδίοΣτατιστικήΣτατιστική
ΟικογένειαHypothesis testHypothesis test
Έτος προέλευσης1969 (first edition); 1988 (definitive second edition)1908
ΔημιουργόςJacob CohenStudent (W. S. Gosset)
ΤύποςStandardized magnitude estimationParametric mean comparison
Θεμελιώδης πηγήCohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832Student (W. S. Gosset) (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗
Εναλλακτικές ονομασίεςeffect magnitude estimation, standardized effect measure, practical significance analysis, ES analysistwo-sample t-test, unpaired t-test, Student t-test, independent groups t-test
Συναφείς44
ΣύνοψηEffect size analysis quantifies the practical magnitude of a statistical result independently of sample size. Rather than asking only whether a difference or relationship is statistically significant, it asks how large it is, using standardized indices such as Cohen's d, eta-squared, omega-squared, or Pearson's r that allow direct comparison across studies and populations.The independent samples t-test is a parametric hypothesis test that determines whether the means of two independent, unrelated groups differ significantly on a continuous outcome variable. Derived from Gosset's 1908 t-distribution, it is one of the most widely used inferential tests in social, behavioral, biomedical, and experimental sciences.
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ScholarGateΣύγκριση μεθόδων: Effect size analysis · Independent samples t-test. Ανακτήθηκε στις 2026-06-18 από https://scholargate.app/el/compare