So sánh phương pháp

	Kiểm định Chi-bình phương Pearson về tính độc lập	Hồi quy Logistic
Lĩnh vực	Thống kê	Thống kê nghiên cứu
Họ	Hypothesis test	Process / pipeline
Năm ra đời	1900	1958
Người khởi xướng	Karl Pearson	David Roxbee Cox
Loại	Nonparametric association / goodness-of-fit	Method
Công trình gốc	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.	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.
Tên gọi khác	chi-squared test, χ² test, Ki-Kare Testi, chi-square test	logit model, binomial logistic regression, LR
Liên quan	3	3
Tóm tắt	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.	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.