least mean squares line
It will minimise the sum of the squared distances from the points to the line of best fit, measured along the axis of the dependent variable.
2
4
4
It is: 9+16 = 25
The line of best fit is also known as the least square line. It uses a statistical technique to determine the line that fits best through a series of scattered data (plots). Using regression analysis, it finds the line that minimizes the amount of errors (deviations - the sum of vertical distance of data points from the line. The result is a unique line that minimizes the total squared deviations, statistically termed the sum of squared errors.
It will minimise the sum of the squared distances from the points to the line of best fit, measured along the axis of the dependent variable.
When the sum of a number plus 3 is squared, it is 11 more than the sum of the number plus 2 when squared.
25
2
3
4
2
2
2
4
4