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Refers to a general estimation technique that selects the parameter value to minimize the squared difference between two quantities, such as the observed value of a variable, and the expected value of that observation conditioned on the parameter value. Gaussian linear models are fit by least squares and least squares is the idea underlying the use of mean-squared-error (MSE) as a way of evaluating an estimator.

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Least Squares Regression Line

I'm in an AP statistics class, and several weeks ago we discussed regression lines. I understand that a regression line is the best fit for the the given data and that it can be used to predict variab …
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