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This lecture introduces linear regression as an important application of the least squares method, focusing on the relationship between X and Y in a linear form. The instructor explains how to find the best-fit line through the least squares solution, minimizing the sum of squared distances between data points and the line. An example is provided to illustrate the calculation process for determining the regression line for a given set of data points.