Least squares is a statistical method used to estimate the parameters of a linear model by minimizing the sum of the squares of the residuals, which are the differences between observed and predicted values. This approach is foundational in regression analysis, particularly in simple linear regression, where it allows for the determination of the best-fitting line through data points by reducing error.
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