Linganisha mbinu

	Urejeshaji wa Njia ya Viwango Vidogo vya Kawaida (OLS)	Kipimo cha Mgeuzo (Ubaguzi)	Mkadiri wa Theil-Sen
Nyanja	Ekonometriki	Takwimu	Takwimu
Familia	Regression model	Regression model	Regression model
Mwaka wa asili	2019	2005	1968
Mwanzilishi	Wooldridge (textbook treatment); classical least squares	Good (2005); Edgington & Onghena (2007); resampling tradition	Henri Theil (1950); P. K. Sen (1968)
Aina	Linear regression	Nonparametric resampling test	Robust linear regression
Chanzo asilia	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792	Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389.
Majina mbadala	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	randomization test, exact permutation test, re-randomization test, Permütasyon Testi	Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator
Zinazohusiana	5	5	6
Muhtasari	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).	The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.	The Theil-Sen estimator is a robust linear regression method that estimates the slope as the median of the slopes computed over all pairs of data points. Introduced by Henri Theil in 1950 and extended by P. K. Sen in 1968, it tolerates outliers in the response with a breakdown point of about 29%.