{"title":"3.。质量管理的统计工具","authors":"Guido Orzes, Alessio Dal Bo","doi":"10.1108/978-1-78769-801-720191003","DOIUrl":null,"url":null,"abstract":"Companies are nowadays called to manage increasingly larger and more complex quantities of data. Making good predictions and estimating a possible risky situation in advance is therefore more important than ever. The statistical tools are a key element to support quality management and production process analyses, allowing managers to anticipate, in various ways, the situations that will arise. After a general introduction to statistics, this chapter discusses the main statistical techniques used to describe, visualize, and analyze data, with particular attention to the methods that allow to verify the quality and consistency of the conclusions (i.e., confidence intervals and hypothesis verification). Finally, some advanced and widespread quality management statistical tools are presented: quality control charts, historical series, and stochastic control.","PeriodicalId":20993,"journal":{"name":"Quality Management: Tools, Methods, and Standards","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"3. Statistical Tools for Quality Management\",\"authors\":\"Guido Orzes, Alessio Dal Bo\",\"doi\":\"10.1108/978-1-78769-801-720191003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Companies are nowadays called to manage increasingly larger and more complex quantities of data. Making good predictions and estimating a possible risky situation in advance is therefore more important than ever. The statistical tools are a key element to support quality management and production process analyses, allowing managers to anticipate, in various ways, the situations that will arise. After a general introduction to statistics, this chapter discusses the main statistical techniques used to describe, visualize, and analyze data, with particular attention to the methods that allow to verify the quality and consistency of the conclusions (i.e., confidence intervals and hypothesis verification). Finally, some advanced and widespread quality management statistical tools are presented: quality control charts, historical series, and stochastic control.\",\"PeriodicalId\":20993,\"journal\":{\"name\":\"Quality Management: Tools, Methods, and Standards\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quality Management: Tools, Methods, and Standards\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/978-1-78769-801-720191003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quality Management: Tools, Methods, and Standards","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/978-1-78769-801-720191003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Companies are nowadays called to manage increasingly larger and more complex quantities of data. Making good predictions and estimating a possible risky situation in advance is therefore more important than ever. The statistical tools are a key element to support quality management and production process analyses, allowing managers to anticipate, in various ways, the situations that will arise. After a general introduction to statistics, this chapter discusses the main statistical techniques used to describe, visualize, and analyze data, with particular attention to the methods that allow to verify the quality and consistency of the conclusions (i.e., confidence intervals and hypothesis verification). Finally, some advanced and widespread quality management statistical tools are presented: quality control charts, historical series, and stochastic control.