However due to experimental error, the relationship between the data collected at different times will rarely be identical. Fitting a straight line through the data in such a way to obtain the fit which most closely reflects the true relationship is, therefore, a widespread need. One well established method is known as the method of least squares. This method can be applied to any polynomial, or even to more general functions, but for the present we shall only consider the linear case. Using iterative method the roots can be found.
Different methods use different criteria to terminate the iteration.
This process is slow to converge. The initial two points must bracket the root for the method to work. In the case of the bisection method it is clear that at each step the interval which surrounds the true value of the root is halved. It may not converge to a root after finite and predictable number of iterations. This process is usually fast to converge.