Minimizing the sum of the squared deviations around the line is called:
A)mean squared error technique.
B)mean absolute deviation.
C)double smoothing.
D)least squares estimation.
E)predictor regression.

Question

Quizplus · Accepted Answer

Minimizing the sum of the squared deviations around the line is known as the least squares estimation. This method is widely used in linear regression to find the best-fitting line through a set of points by minimizing the sum of the squares of the vertical distances of the points from the line.

Minimizing the Sum of the Squared Deviations Around the Line