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A statistical procedure that estimated regression equation coefficients that produce the lowest sum of squared differences between the actual and predicted values of the dependent variable is called .

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Answer:

Ordinary least squares

Step-by-step explanation:

The ordinary least squares means the estimations that done for parameters in a regression model by lowering the sum of the square residuals. It also predicted the coefficient of the regression equation that generate the actual and the expected values of the dependent variable is known as ordinary least squares

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