Least Squares 2a

①This example demonstrates linear regression fitting of discrete data points using the method of least squares in a coordinate plane, visually showing the geometric meaning of minimizing the sum of squared residuals. ②Core mathematical concepts include least squares, linear regression, residuals (vertical distances), sum of squares optimization, and the geometric relationship between the fitted line and data points. ③Construction details: Uses GeoGebra commands Plane and Segment; objects include data points P1, P2, P3, weights w1, w2, vector v0, origin O, fitted line p, slope m, intercept b, and residual segments r1, r2, r3, etc., allowing dynamic adjustment of parameters to observe fitting effects. ④Suitable for high school to early college mathematics or statistics courses, helping students understand the principles of regression analysis and visually verify the optimization process of least squares.