{"title":"理解贝叶斯统计。","authors":"Mitchell G Maltenfort","doi":"10.1097/BSD.0000000000000320","DOIUrl":null,"url":null,"abstract":"<p><p>Modern computing power has given us the ability to approach statistical questions in a manner which was previously impossible because of the time-consuming nature of the calculations required. Computer power has enabled the use of Bayesian inference techniques, based on 18th century theory, to frame statistical questions in probability. </p>","PeriodicalId":50043,"journal":{"name":"Journal of Spinal Disorders & Techniques","volume":"28 8","pages":"294"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1097/BSD.0000000000000320","citationCount":"0","resultStr":"{\"title\":\"Understanding Bayesian Statistics.\",\"authors\":\"Mitchell G Maltenfort\",\"doi\":\"10.1097/BSD.0000000000000320\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Modern computing power has given us the ability to approach statistical questions in a manner which was previously impossible because of the time-consuming nature of the calculations required. Computer power has enabled the use of Bayesian inference techniques, based on 18th century theory, to frame statistical questions in probability. </p>\",\"PeriodicalId\":50043,\"journal\":{\"name\":\"Journal of Spinal Disorders & Techniques\",\"volume\":\"28 8\",\"pages\":\"294\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1097/BSD.0000000000000320\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Spinal Disorders & Techniques\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1097/BSD.0000000000000320\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Spinal Disorders & Techniques","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/BSD.0000000000000320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q","JCRName":"Medicine","Score":null,"Total":0}
Modern computing power has given us the ability to approach statistical questions in a manner which was previously impossible because of the time-consuming nature of the calculations required. Computer power has enabled the use of Bayesian inference techniques, based on 18th century theory, to frame statistical questions in probability.
期刊介绍:
Journal of Spinal Disorders & Techniques features peer-reviewed original articles on diagnosis, management, and surgery for spinal problems. Topics include degenerative disorders, spinal trauma, diagnostic anesthetic blocks, metastatic tumor spinal replacements, management of pain syndromes, and the use of imaging techniques in evaluating lumbar spine disorder. The journal also presents thoroughly documented case reports.