The Precision Paradox: Why Higher-Order Interpolation Isn't Always Better

This analysis explores the mathematical reality of table-based interpolation: beyond a certain degree, using more interpolation points doesn't improve accuracy and can actually harm it due to exponential growth in error coefficients. The Lagrange interpolation theorem demonstrates that optimal precision depends on balancing table spacing and data precision, a lesson critical for numerical computing, scientific calculations, and engineering applications.