Question: Least squares regression finds the estimated values for the parameters in a regression model to minimize Why is it necessary to square the estimation errors?

Least squares regression finds the estimated values for the parameters in a regression model to minimize

Why is it necessary to square the estimation errors? What problem might be encountered if we attempt to minimize just the sum of the estimationerrors?

- Y)2: ESS = i (Y;

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