Confronta i metodi

	Test Chi-quadro di Indipendenza	Regressione Logistica
Campo	Statistica	Statistica per la ricerca
Famiglia	Hypothesis test	Process / pipeline
Anno di origine	1900	1958
Ideatore	Karl Pearson	David Roxbee Cox
Tipo	Nonparametric test of association	Method
Fonte seminale	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
Correlati	2	3
Sintesi	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.