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校准线法定量在分析化学中应用广泛,实际样品的测定结果大多是通过与作为标准已知量的校准线进行比较而求得的,校准线的精确性直接影响着样品测定结果的准确性。因此,探讨提高校准线精确性的回归和检验方法显得更加重要。1 现行回归和检验方法存在的缺陷公认的校准线回归方法是以设定的校准线y=ax+b的统计量y_i(y_i=ax_i+b)与标准溶液系列x_i的实测值y_i之间的绝对偏差△_i=y_i-y_i的绝对值|△_i|=|y_i-y_i|为回归参数,采用最小二乘法,即求∑(y_i-y_i)~2的极小值,从而确定所设校准线方程中的系数a和b,它们的值分别为
The calibration line method is widely used in analytical chemistry. The actual measurement results of the actual samples are mostly obtained by comparing with the calibration lines as the standard known quantities. The accuracy of the calibration lines directly affects the accuracy of the determination results of the samples. Therefore, it is even more important to explore regression and test methods to improve the accuracy of calibration lines. 1 existing regression and test methods exist defects recognized calibration line regression method is based on the set calibration line y = ax + b statistics y_i (y_i = ax_i + b) and the standard solution series x_i measured y_i Absolute deviation △ _i = the absolute value of y_i-y_i | △ _i | = | y_i-y_i | as regression parameters, using the least squares method, that is, find the minimum value of Σ (y_i-y_i) ~ 2, The coefficients a and b in the line equation, respectively, are