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Least Squares Fitting
The document discusses the least squares method for fitting curves and lines to datasets. It begins by introducing least squares methods and their applications. It then covers the history of least squares, which was first published by Legendre in 1805 and also developed by Gauss. The document goes on to explain how least squares finds the "best fit" line or curve by minimizing the sum of the squared residuals between the data points and the fitting curve. It provides the equations for computing the coefficients of a linear regression line using the least squares approach. Finally, it generalizes the method to fitting polynomials of various degrees to data.
