Comparer des méthodes

	Test du Khi-deux d'indépendance	Régression logistique
Domaine	Statistique	Statistiques de recherche
Famille	Hypothesis test	Process / pipeline
Année d'origine	1900	1958
Auteur d'origine	Karl Pearson	David Roxbee Cox
Type	Nonparametric test of association	Method
Source fondatrice	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.	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.
Alias	chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi	logit model, binomial logistic regression, LR
Apparentées	2	3
Résumé	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.	Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.