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In this paper we do the analogical study of two different numerical methods in respect to iteration. Any numerical analysis model or method is faster if and only if a sequence of model solutions with increasingly refined solution domains approaches to a fixed value. Newton�Raphson and False Position methods are very e?ective numerical procedures used for solving nonlinear equations of the form f(x) = 0.Their analyses can be carried out from comparing Newton-Raphson and False Position. Given that a model is consistent, it is not feasible to apply any method to a problem without testing the size of the time and iterative steps which form the discrete approximation of the solution of the given problem. And we can say that Newton Raphson is best and faster than False Position method. The contents of this note should also be a useful exercise/example in the application of polynomial interpolation and divided di?erences in introductory courses in numerical analysis.