Least squares fitting is a mathematical method used to determine the best-fitting curve or line through a set of data points by minimizing the sum of the squares of the differences between the observed values and those predicted by the model. This technique is commonly applied in statistical analysis and data modeling to estimate parameters of non-linear functions, ensuring that the overall deviation of the fitted model from the actual data is minimized.
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