Bayesian Reasoning in Data Analysis is popular PDF and ePub book, written by Giulio D'Agostini in 2003, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Bayesian Reasoning in Data Analysis can be Read Online from any device for your convenience.
Bayesian Reasoning in Data Analysis Book PDF Summary
This book provides a multi-level introduction to Bayesian reasoning (as opposed to OC conventional statisticsOCO) and its applications to data analysis. The basic ideas of this OC newOCO approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference; combination of results; treatment of uncertainty due to systematic errors and background; comparison of hypotheses; unfolding of experimental distributions; upper/lower bounds in frontier-type measurements. Approximate methods for routine use are derived and are shown often to coincide OCo under well-defined assumptions! OCo with OC standardOCO methods, which can therefore be seen as special cases of the more general Bayesian methods. In dealing with uncertainty in measurements, modern metrological ideas are utilized, including the ISO classification of uncertainty into type A and type B. These are shown to fit well into the Bayesian framework.
Detail Book of Bayesian Reasoning in Data Analysis PDF
- Author : Giulio D'Agostini
- Release : 30 September 2024
- Publisher : World Scientific
- ISBN : 9789812775511
- Genre : Mathematics
- Total Page : 351 pages
- Language : English
- PDF File Size : 12,9 Mb
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