Võrdle meetodeid

	Jõudluse analüüs proportsioonitestide jaoks	Pearsoni chi-ruut sõltumatustest
Valdkond	Statistika	Statistika
Perekond	Hypothesis test	Hypothesis test
Tekkeaasta	1988	1900
Looja	Jacob Cohen	Karl Pearson
Tüüp	Sample size determination	Nonparametric test of association
Algallikas	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates.	Pearson, 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.
Rööpnimetused	proportion power analysis, two-proportion z-test power, z-test for proportions power, Oran Testi Güç Analizi	chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi
Seotud	3	2
Kokkuvõte	Power analysis for proportion tests is a prospective sample-size planning method used to determine how many participants are needed to detect a meaningful difference between two (or one) proportions with a specified probability. Formalised by Jacob Cohen in his 1988 landmark text, it applies the arcsine transformation to convert proportions into the effect-size index h, enabling direct calculation of the required sample size.	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.