What is the name of the method used to find the line of best fit?

Question

What is the name of the method used to find the line of best fit?

Answer 1

The method is called "least squares". The best fit in the least-squares sense is that instance of the model for which the sum of squared residuals has its least value.

(A residual being the difference between an observed value and the value given by the model)



See this link : http://en.wikipedia.org/wiki/Least_squares

Answer 2

There are many ways to fit a line to data. Linear regression is the most common. A point and a slope specify a unique line, of course. Linear regression implies the use of a particular method that determines a line that goes through the average of the data and uses a least squared fit to determine the slope.



Least squared fits are used for any curve, not just a line.



http://en.wikipedia.org/wiki/Linear_regression

Answer 3

Linear regression is what you are looking for. A linear regression equation is formed by considering the data, and then forming a line through the most applicable points. You can usually find this on a Texas Instruments TI 83 or 84 plus graphing calculator.

Push STAT

---->Go right and select CALC

------->Go down to select LinReg.

Enter that, and you will be given an equation for the best fit line.

This equation will not graph itself until you either manually program it into the Y= box, or have your calculator do it.

Answer 4

Least squares is the most common one used. It measures the magnitude of the difference between each point on the curve and the corresponding point on the line. The best fit line is the one with the smallest total for that discrepancy. (They use a square of the discrepancy to avoid plus and minus values canceling each other out).

Answer 5

Least squares regression