{"title":"模拟中的零假设显著性检验","authors":"Marko A. Hofmann","doi":"10.1109/WSC.2016.7822118","DOIUrl":null,"url":null,"abstract":"Several papers have recently criticized the use of null hypothesis significance testing (NHST) in scientific applications of stochastic computer simulation. Their criticism can be underpinned by numerous articles from statistical methodologists. They have argued that focusing on p-values is not conducive to science, and that NHST is often dangerously misunderstood. A critical reflection of the arguments contra NHST shows, however, that although NHST is indeed ill-suited for many simulation applications and objectives it is by no means superfluous, neither in general, nor in particular for simulation.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Null hypothesis significance testing in simulation\",\"authors\":\"Marko A. Hofmann\",\"doi\":\"10.1109/WSC.2016.7822118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Several papers have recently criticized the use of null hypothesis significance testing (NHST) in scientific applications of stochastic computer simulation. Their criticism can be underpinned by numerous articles from statistical methodologists. They have argued that focusing on p-values is not conducive to science, and that NHST is often dangerously misunderstood. A critical reflection of the arguments contra NHST shows, however, that although NHST is indeed ill-suited for many simulation applications and objectives it is by no means superfluous, neither in general, nor in particular for simulation.\",\"PeriodicalId\":367269,\"journal\":{\"name\":\"2016 Winter Simulation Conference (WSC)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Winter Simulation Conference (WSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WSC.2016.7822118\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC.2016.7822118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Null hypothesis significance testing in simulation
Several papers have recently criticized the use of null hypothesis significance testing (NHST) in scientific applications of stochastic computer simulation. Their criticism can be underpinned by numerous articles from statistical methodologists. They have argued that focusing on p-values is not conducive to science, and that NHST is often dangerously misunderstood. A critical reflection of the arguments contra NHST shows, however, that although NHST is indeed ill-suited for many simulation applications and objectives it is by no means superfluous, neither in general, nor in particular for simulation.