The Mismeasurement
Six Numbers Every Investor Must Know eBooks & eLearning
Posted by ELK1nG at June 27, 2022
Six Numbers Every Investor Must Know
Published 6/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.11 GB | Duration: 1h 51m
Published 6/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.11 GB | Duration: 1h 51m
Making sense of Return, Risk, Diversification, Valuation, Leverage and Expenses
Mildred Trotter and the Invisible Histories of Physical and Forensic Anthropology eBooks & eLearning
Posted by Sigha at May 9, 2022
Mildred Trotter and the Invisible Histories of Physical and Forensic Anthropology
English | 2022 | ISBN: 1032180900 | 232 pages | True PDF | 4.51 MB
English | 2022 | ISBN: 1032180900 | 232 pages | True PDF | 4.51 MB
Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application eBooks & eLearning
Posted by AvaxGenius at Aug. 2, 2017
Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application By Grace Y. Yi
English | PDF | 2017 | 497 Pages | ISBN : 1493966383 | 4.67 MB
This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies.
Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application eBooks & eLearning
Posted by AvaxGenius at Dec. 11, 2019
Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application By Grace Y. Yi
English | EPUB | 2017 | 497 Pages | ISBN : 1493966383 | 4.54 MB
This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies.