Σύγκριση μεθόδων

	Έλεγχος Ανεξαρτησίας Chi-square	Λογιστική Παλινδρόμηση
Πεδίο	Στατιστική	Ερευνητική Στατιστική
Οικογένεια	Hypothesis test	Process / pipeline
Έτος προέλευσης	1900	1958
Δημιουργός	Karl Pearson	David Roxbee Cox
Τύπος	Nonparametric test of association	Method
Θεμελιώδης πηγή	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.
Εναλλακτικές ονομασίες	chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi	logit model, binomial logistic regression, LR
Συναφείς	2	3
Σύνοψη	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.