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Newton's backward interpolation formula is used to estimate the value of a function at a point within a given range of discrete data points, particularly when the desired point is near the end of the dataset. It employs divided differences based on the values of the function at these data points, using the most recent points for interpolation. This technique is especially useful when dealing with equally spaced data, allowing for efficient computation of interpolated values. Common applications include numerical analysis, engineering, and computer graphics where precise function estimation is required.

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What is Newton's backward interpolation formula?

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