大数据背景下产品质量抽样调查的样本量设计  

Sample Size Design of Product Quality Sampling Survey Under the Background of Big Data

作　　者：张璇 赵静 丁文兴[1] ZHANG Xuan;ZHAO Jing;DING Wenxing(China National Institute of Standardization,Beijing 100191)

机构地区：[1]中国标准化研究院,北京100191

出　　处：《系统科学与数学》2022年第1期133-140,共8页Journal of Systems Science and Mathematical Sciences

基　　金：全国市场监管执法稽查数据分析服务(522021C-8620);定量快速检测方法的统计评估与确认技术研究(522020Y-7475)资助课题。

摘　　要：产品质量抽样调查是政府质量监督部门监管产品质量状况的重要手段,在历年的产品质量抽样调查中,也累积了大量的实际数据.文章将大量数据提供的先验信息和抽样调查中的样本量设计进行了有效的结合,利用大数据提供的有价值信息作为辅助信息,使用聚类等方法对调查对象进行分层,根据各层的不同特点利用优先数系确定各层间相对误差限的关系,进而确定分层随机抽样样本量,使得样本量确定方式兼顾了科学和实用的优点.同时,通过对不同层的监督总体选取不同水平的参数,在调查费用有限的条件下,提高了监督的有效性.Product quality sampling survey is an important means for government quality supervision department to know the product quality status.In the sampling survey of product quality over the years,a large number of actual data have also been accumulated.In this paper,the prior information provided by big data is effectively combined with the sample size design in sampling survey.The valuable information provided by big data is used as auxiliary information,and the survey objects are stratified by clustering method.According to the different characteristics of each stratum,the relationship between relative error limits of each stratum is determined by the series of preferred numbers,and then the stratified random sampling sample size is determined,which makes the determination method of sample size be taken into account the advantages of science and practicality.At the same time,by selecting different levels of parameters for different strata of supervision objects,the effectiveness of supervision is improved under the condition of limited cost.

关 键 词：大数据 产品质量 抽样调查 样本量 优先数系 

分 类 号：F203[经济管理—国民经济]