방법 비교

	코헨의 카파 계수	카이제곱 독립성 검정	맥니마르 검정
분야	통계학	통계학	통계학
계열	Hypothesis test	Hypothesis test	Hypothesis test
기원 연도	1960	1900	1947
창시자	Jacob Cohen	Karl Pearson	Quinn McNemar
유형	Inter-rater reliability coefficient	Nonparametric test of association	Nonparametric test for paired binary data
원전	Cohen, J. (1960). A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 20(1), 37–46.	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.	McNemar, Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2), 153–157.
별칭	kappa coefficient, kappa statistic, Cohen's Kappa (Değerlendiriciler Arası Uyum)	chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi	McNemar chi-square test, test for correlated proportions, paired binary test, McNemar Testi
관련	3	2	5
요약	Cohen's kappa (κ) is a statistical measure of inter-rater reliability for categorical classifications, introduced by Jacob Cohen in 1960. Unlike simple percent agreement, kappa corrects for the level of agreement that would be expected purely by chance, making it the standard metric when two raters independently assign observations to the same set of mutually exclusive categories.	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.	McNemar's test is a nonparametric hypothesis test that compares two paired (correlated) binary proportions, such as a yes/no measurement taken on the same subjects before and after an intervention. It was introduced by Quinn McNemar in 1947 and works on the 2×2 table of matched outcomes.