![]() ![]() After some curricular changes, including GR tool adopted in class, several objectives such as failure rate decrease (60% to 15%), notably motivation and enhancement increase (Likert's test), and development of logic-mathematics reasoning, among others, could be reached. Such tool was used in the " introduction to engineering " subject at up to 2014, this subject's failure rate was very high (near 60%) in which traditional teaching method was used. Results about a mathematical tool, called Generic Rectangle (GR), applied in a preparatory course in order to resolve algebraic problems such as multiplying binomials and factoring quadratics are shown. They conclude that Newton-Raphson method is 7.6786 times better than the bisection method while Secant method is 1.3894 times better than Newton method. They observed that rate of convergence is in the following order: Bisection Methods < Newton-Raphson < Secant Method. In comparing the rate of convergence if Bisection, Secant and Newton-Raphson methods used C++ program language to calculate cube root of number from 1 to 25, using the three methods. In Newton-Raphson, the derivation of a function at a point is used to create the tangent line, whereas in Secant method, a numerical approximation of the derivative based on two points is used to create the secant line. The difference is that Newton-Raphson method uses a line that is tangent to one point, while the Scent method uses a line that is secant to two points. As Secant method and Newton-Raphson method are almost same, from geometric perspective. An algorithm that converges quickly but takes a few second per iteration may take more time overall than an algorithm that converges more slowly, but takes a few milliseconds per iteration. It can be seen that Newton-Raphson may converge faster than any other method but when we compare the performance, it is needful to consider both cost and speed of convergence. The whole study is comparing the rate of performance of Bisection, and Newton-Raphson methods of finding roots. ![]() The higher the order, the faster the method converges. The rate of convergence could be linear, quadratic or otherwise. That is Some methods are faster in converging to the roots than others. Different methods converge the roots at different rates. It arises in a wide variety of practical application in Physics, Chemistry, Biosciences, etc. The root finding problem is one of the most relevant computational problem. In this paper we are going to get detail information about the different methods such as Bisection, Secant and Newton-Raphson methods and the difference between the ways of solving and the difference between each of them. INTRODUCTION The fact that the roots of the polynomial can be obtained immediately using computer program as MATLAB, does not diminish the importance of gaining the new ways for solving the polynomial equation, simpler than that of current ones. ![]() We will get to know how these methods differ from each other I. At the conclusion we will elaborate on the differences in solving a particular polynomial equation by using variety of method, what are the differences among these methods and difficulty level of them. Less time consumption and easiness of solving equation can be brought by changing variable and by some small change in calculation. These methods are evolving and improved on regular basis. There are some different method to solve the same problem but the question arises that which method is better, more time efficient and more accurate. We are going to study three methods i.e, equation by Bisection, Regular-Falsi and Newton-Raphson methods and how these methods differ from each other. In this research paper we are going to detail about how to calculate approximate value of roots of the polynomial equation by different ways. ![]()
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