ScholarGate
Avustaja

Vertaile menetelmiä

Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.

Vaikutuksen koon analyysi×Riippumattomien otosten t-testi×
TieteenalaTilastotiedeTilastotiede
MenetelmäperheHypothesis testHypothesis test
Syntyvuosi1969 (first edition); 1988 (definitive second edition)1908
KehittäjäJacob CohenStudent (W. S. Gosset)
TyyppiStandardized magnitude estimationParametric mean comparison
AlkuperäislähdeCohen, 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 ↗
Rinnakkaisnimeteffect magnitude estimation, standardized effect measure, practical significance analysis, ES analysistwo-sample t-test, unpaired t-test, Student t-test, independent groups t-test
Liittyvät44
TiivistelmäEffect 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.
ScholarGateAineisto
  1. v1
  2. 2 Lähteet
  3. PUBLISHED
  1. v1
  2. 2 Lähteet
  3. PUBLISHED

Siirry hakuun Lataa diat

ScholarGateVertaile menetelmiä: Effect size analysis · Independent samples t-test. Haettu 2026-06-18 osoitteesta https://scholargate.app/fi/compare