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 .

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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step-by-step explanation:

if you want to solve percent error follow these steps.

1. subtract the accepted value from the experimental value.

2. take the absolute value of step 1.

3. divide that answer by the accepted value.

4. multiply that answer by 100 and add the % symbol to express the answer as a percentage.

if you want to solve percent of change just do this.

1. work out the difference (increase) between the two numbers you are comparing.

2. divide the increase by the original number and multiply the answer by 100. if your answer is a negative number then this is a percentage decrease.

hope this : )

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step-by-step explanation: