Data smoothing is a statistical technique aimed at reducing noise in a dataset, allowing significant patterns and trends to emerge more clearly. This involves generating a smooth curve that approximates the data points, employing methods such as moving averages, exponential smoothing, and LOESS (Locally Estimated Scatterplot Smoothing). Data smoothing is particularly beneficial for analysts and researchers seeking to identify trends and extract meaningful insights from noisy or irregular data, facilitating better decision-making and understanding of underlying patterns.
