So sánh phương pháp

	Kiểm định Durbin-Watson về Tự tương quan	Hồi quy Bình phương Tối thiểu Thông thường (OLS)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1950	2019
Người khởi xướng	James Durbin & Geoffrey Watson	Wooldridge (textbook treatment); classical least squares
Loại	Test for first-order residual autocorrelation	Linear regression
Công trình gốc	Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression: I. Biometrika, 37(3/4), 409–428.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Tên gọi khác	DW test, Durbin-Watson statistic, Durbin-Watson otokorelasyon testi	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Liên quan	4	5
Tóm tắt	The Durbin-Watson test, developed by James Durbin and Geoffrey Watson in 1950–1951, detects first-order serial correlation in the residuals of a linear regression. Its statistic ranges from 0 to 4, with a value near 2 indicating no autocorrelation, values toward 0 indicating positive autocorrelation, and values toward 4 indicating negative autocorrelation. It remains one of the most reported regression diagnostics despite well-known limitations.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).