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OblastStatistikaStatistika
PorodicaHypothesis testHypothesis test
Godina nastanka1969 (1st ed.); 1988 (seminal 2nd ed.)1900
TvoracJacob CohenKarl Pearson
TipSample size and power planningNonparametric test of association
Temeljni izvorCohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157–175. DOI ↗
Drugi nazivisample size calculation, power calculation, sensitivity analysis, a priori power analysischi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi
Srodne52
SažetakPower 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.The chi-square test of independence is a nonparametric hypothesis test that examines whether two categorical variables are associated by comparing observed and expected frequencies in a cross-tabulation. It rests on the chi-square criterion introduced by Karl Pearson in 1900.
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ScholarGateUporedite metode: Power analysis · Chi-square test. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare