Abstract
Today's software offers more for numerical analysis than just programming. The software MATLAB can be used to do things the traditional way; writing loops; branching using logical decisions and invoking subroutines. Now a larger programming environment is available; graphics and built in subroutine libraries. These features are influencing the way numerical analysis is taught. MATLAB is based on lists and many algorithms can be streamlined by taking advantage of this structure. Graphical output for interpolation, curve fitting and the solution of differential equations is easily produced by manipulating these data structures. This article illustrates how MATLAB can be used in a numerical analysis course to enhance the teaching of: Newton's method, Gaussian elimination, Chebyshev approximation, least squares polynomials, error analysis for numerical differentiation, adaptive quadrature, Runge‐Kutta methods, and the solution of Laplace's equation. Our students have enjoyed MATLAB, and had a better experience computing with it. They were able to explore more algorithms given in the textbook and use several state of the art algorithms that are built into MATLAB.
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