Sammenlign metoder

	Two-proportion z-test	Chi-kvadrat-test for uafhængighed
Fagområde	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test
Oprindelsesår	1900	1900
Ophavsperson	Karl Pearson / classical large-sample z approximation	Karl Pearson
Type	Parametric proportion comparison	Nonparametric test of association
Oprindelig kilde	Fleiss, J. L., Levin, B., & Paik, M. C. (2003). Statistical Methods for Rates and Proportions (3rd ed.). Wiley.	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.
Aliasser	z-test for proportions, two-sample proportion test, one-proportion z-test, Oran Testi — z Testi (Oranlar)	chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi
Relaterede	4	2
Resumé	The proportion test (z-test for proportions) is a parametric hypothesis test that compares one or two sample proportions against a reference value or each other. Grounded in the large-sample normal approximation formalized by Fleiss, Levin, and Paik (2003), it is the standard tool for binary outcome comparisons when samples are large enough for the central limit theorem to apply.	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.