Central difference is a numerical method used to approximate the derivative of a function by utilizing values of the function at points around a specific point. This method is particularly effective because it takes into account information from both sides of the point, which typically provides a more accurate estimate of the derivative compared to forward or backward difference methods. The central difference approach is crucial in finite difference schemes, numerical differentiation, and solving partial differential equations.
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