Sammenlign metoder

	Effektstørrelsesanalyse	Power-analyse
Fagområde	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test
Oprindelsesår	1969 (first edition); 1988 (definitive second edition)	1969 (1st ed.); 1988 (seminal 2nd ed.)
Ophavsperson	Jacob Cohen	Jacob Cohen
Type	Standardized magnitude estimation	Sample size and power planning
Oprindelig kilde	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
Aliasser	effect magnitude estimation, standardized effect measure, practical significance analysis, ES analysis	sample size calculation, power calculation, sensitivity analysis, a priori power analysis
Relaterede	4	5
Resumé	Effect 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.	Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (alpha), and statistical power (1 minus beta) — so that researchers can determine the sample size needed before data collection or evaluate the sensitivity of a completed study.