李志平,吴雄杰,赵康,方强,金仲,汪佳,江小平.溶剂残留（甲苯）校准回归方程的建立及评价[J].包装工程,2017,38(9):59-64.
LI Zhi-ping,WU Xiong-jie,ZHAO Kang,FANG Qiang,JIN Zhong,WANG Jia,JIANG Xiao-ping.Establishment and Evaluation of Calibration Regression Equation for Residual Solvent (Methylbenzene)[J].Packaging Engineering,2017,38(9):59-64. |
| 溶剂残留（甲苯）校准回归方程的建立及评价 |
| Establishment and Evaluation of Calibration Regression Equation for Residual Solvent (Methylbenzene) |
| 投稿时间：2016-07-21 修订日期：2017-05-10 |
| DOI： |
| 中文关键词: 甲苯 普通最小二乘法 加权最小二乘法 校准回归方程 残留物检测 |
| 英文关键词: methylbenzene ordinary least square method weighted least square method calibration regression equation detection of residues |
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| 中文摘要: |
| 目的 为了提高溶剂残留检测水平，以溶剂残留中的甲苯为例详细说明校准回归方程的建立以及评价方法。方法 以GB/T 10004—2008中溶剂残留分析方法为基础，建立甲苯加权最小二乘法校准回归方程，并通过判定系数、标准差、统计检验、置信区间、控制限、线性范围、不确定度对加权校准回归方程进行系统综合评价，对普通与加权最小二乘法得到的校准回归方程的实际回归效果进行比较。结果 加权校准回归方程模型恰当、线性显著、拟合程度高，能有效消除异方差对校准回归方程的影响，显著降低低浓度测定时的相对误差，保证测量结果的精确性、可靠性。结论 文中方法对于实验室进行校准回归方程的建立和评价、质量控制以及数据处理和分析具有一定的指导意义。 |
| 英文摘要: |
| The work aims to study the building and evaluation methods of calibration regression equation for methylbenzene in solvent residues in order to improve the test level of solvent residues. Based on the analysis method for solvent residues in GB/T 10004—2008, the weighted least square method of methylbenzene was adopted to establish the calibration regression equation. The weighted calibration regression equation was evaluated systematically and comprehensively through coefficient of determination, standard deviation, statistical test, confidence interval, control limits, linear range and uncertainty. The practical regression effects of calibration regression equations obtained in ordinary and weighted least square methods were compared. The weighted calibration regression equation model was appropriate and of significant linearity and remarkable fitting degree. It could effectively eliminate the effects of heteroscedasticity on the calibration regression equation, reduce the relative error in low-concentration determination significantly, and ensure the accuracy and reliability of the test results. The proposed method can be important guide for the building and evaluation of calibration regression equation, quality control and processing and analysis of data in the laboratory. |
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