Data smoothing is a statistical technique used to reduce noise in a dataset by creating a smoother representation of the underlying trends. This process helps to highlight important patterns while minimizing fluctuations caused by random variations or measurement errors. In spline interpolation, data smoothing plays a crucial role in generating curves that approximate the data points without being overly influenced by irregularities.
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