Least squares is a statistical method used to minimize the differences between observed values and those predicted by a model. This technique is fundamental in regression analysis, particularly in finding the best-fitting line through a set of data points. By minimizing the sum of the squares of these differences, least squares helps identify relationships and trends in data, which is essential for both linear and nonlinear trend models.
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