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Analīze efektu lielumam×Vienvirziena dispersijas analīze×
NozareStatistikaStatistika
SaimeHypothesis testHypothesis test
Izcelsmes gads1969 (first edition); 1988 (definitive second edition)1925
AutorsJacob CohenRonald A. Fisher
TipsStandardized magnitude estimationParametric mean comparison
PirmavotsCohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗
Citi nosaukumieffect magnitude estimation, standardized effect measure, practical significance analysis, ES analysisone-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Saistītās44
KopsavilkumsEffect 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.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.
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ScholarGateSalīdzināt metodes: Effect size analysis · One-way ANOVA. Izgūts 2026-06-18 no https://scholargate.app/lv/compare