Probability and Statistics
The least squares criterion is a mathematical approach used to minimize the differences between observed values and the values predicted by a model. This method helps in finding the best-fitting line or curve for a given set of data by minimizing the sum of the squares of these differences, known as residuals. It's widely applied in regression analysis to determine the parameters that best explain the relationship between variables.
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