Sammenlign metoder

	Pearsons kikelighedstest for uafhængighed	Cramérs V	McNemar-testen
Fagområde	Statistik	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test	Hypothesis test
Oprindelsesår	1900	1946	1947
Ophavsperson	Karl Pearson	Harald Cramér	Quinn McNemar
Type	Nonparametric association / goodness-of-fit	Nonparametric association measure	Nonparametric test for paired binary data
Oprindelig kilde	Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables. Philosophical Magazine, Series 5, 50(302), 157–175.	Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press. ISBN: 978-0691080420	McNemar, Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2), 153–157.
Aliasser	chi-squared test, χ² test, Ki-Kare Testi, chi-square test	cramers v, cramer v, phi coefficient (r×c), Cramer's V (İlişki Kuvveti)	McNemar chi-square test, test for correlated proportions, paired binary test, McNemar Testi
Relaterede	3	3	5
Resumé	The chi-square test of independence is a nonparametric hypothesis test that determines whether two categorical variables are statistically associated or independent of one another. Introduced by Karl Pearson in 1900, it remains the standard procedure for analysing contingency tables and requires no assumption of normality — only that observations are independent and that expected cell frequencies are sufficiently large.	Cramer's V is a nonparametric effect-size statistic that measures the strength of association between two categorical variables on a scale from 0 to 1. Introduced by the Swedish mathematician Harald Cramér in his 1946 work Mathematical Methods of Statistics, it generalises the phi coefficient to tables of any size, making it the standard companion statistic to the chi-square test.	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.