最小平方近似法 (least-squares approximation) 是用來求出一組離散 (discrete) 數據點的近似函數 (approximating function)，作實驗所得的數據亦常使用最小平方近似法來達成曲線密合 (curve fitting)。以下所介紹的最小平方近似法是使用多項式作為近似函數，除了多項式之外，指數、對數方程式亦可作為近似函數。關於最小平方近似法的計算原理，請參閱市面上的數值分析書籍-least square approximation (least-squares approximation) to get a group of discrete (discrete) data point to the approximate function (approximating function), the experimental data are often using the least square approximation to reach a secret curve (curve fitting) . Outlined below are the least square approximation is used as a polynomial approximation functions, in addition to polynomials, the index several right formula may be used as a similar function. On the smallest square approximation calculation principles, please refer to the numerical analysis of the market books