Linear Regression Example 2 by Anthony Panontin

This example demonstrates how to construct a linear regression model from a set of scattered points in a Cartesian coordinate system and draw the best-fit regression line, illustrating the orthogonal projection relationship between data points and the regression line. Core mathematical concepts include linear regression, least-squares fitting, function graphing, analytic geometry line equations, orthogonal projection, and polygon construction. The construction uses GeoGebra commands Line, OrthogonalLine, Intersect, Polygon, Sum, and FitLineY, together with point objects A through R, line objects a through s, and polygon objects poly1 through poly4, building auxiliary geometric structures through intersections and polygons. Suitable for high school statistics and functions instruction, as well as university introductory data analysis and geometric modeling inquiry-based learning.