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Erinevusmeetodeid, known in English as difference methods, are numerical techniques used to approximate solutions to differential equations. These methods work by discretizing the continuous domain of the problem into a grid of points. At each grid point, the derivatives in the differential equation are replaced by approximations based on the values of the solution at neighboring points.

The most common difference methods include the forward difference, backward difference, and central difference methods. The forward difference method uses the value at the current point and a point ahead to approximate the derivative. The backward difference method uses the current point and a point behind. The central difference method, often more accurate, uses points on both sides of the current point.

The choice of difference method and the spacing of the grid points (step size) significantly impact the accuracy and stability of the numerical solution. Smaller step sizes generally lead to more accurate approximations but require more computational resources. Error analysis is crucial in difference methods to understand the convergence of the numerical solution to the true solution as the step size approaches zero.

Difference methods are widely applied in various scientific and engineering fields, including fluid dynamics, heat transfer, structural analysis, and finance, for solving problems that cannot be solved analytically. They form the foundation for many numerical simulation tools.