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Titlebook: Elements of Probability and Statistics; An Introduction to P Francesca Biagini,Massimo Campanino Textbook 2016 Springer International Publi

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樓主
發(fā)表于 2025-3-21 16:29:21 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Elements of Probability and Statistics
副標(biāo)題An Introduction to P
編輯Francesca Biagini,Massimo Campanino
視頻videohttp://file.papertrans.cn/308/307630/307630.mp4
概述Provides an introduction to elementary probability and to Bayesian statistics using de Finetti‘s subjectivist approach.Introduces as fundamental the concept of random numbers.Includes numerous exercis
叢書名稱UNITEXT
圖書封面Titlebook: Elements of Probability and Statistics; An Introduction to P Francesca Biagini,Massimo Campanino Textbook 2016 Springer International Publi
描述.This?book provides an introduction to elementary probability?and to Bayesian statistics using?de Finetti‘s subjectivist approach. One of the features of this approach is that it does not require the?introduction of?sample space –?a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate –?but introduces as fundamental the concept of random numbers directly related to their?interpretation in applications. Events become a particular case of random?numbers and probability a particular case of expectation when it is?applied to events. The subjective evaluation of expectation and of?conditional expectation is based on an economic choice of an acceptable?bet or penalty.?The properties of expectation and conditional expectation?are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics..
出版日期Textbook 2016
關(guān)鍵詞Bayesian statistics; Conditional expectation; Logical dependence; Markov chains; Probability
版次1
doihttps://doi.org/10.1007/978-3-319-07254-8
isbn_softcover978-3-319-07253-1
isbn_ebook978-3-319-07254-8Series ISSN 2038-5714 Series E-ISSN 2532-3318
issn_series 2038-5714
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 23:10:34 | 只看該作者
2038-5714 has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics..978-3-319-07253-1978-3-319-07254-8Series ISSN 2038-5714 Series E-ISSN 2532-3318
板凳
發(fā)表于 2025-3-22 01:33:58 | 只看該作者
One-Dimensional Absolutely Continuous DistributionsFor random numbers with discrete distribution, the distribution is completely specified by the probabilities of taking single values. If we want to introduce random numbers that take values on intervals or on the whole line, then the specification of the probabilities of taking single values is no longer sufficient to determine their distributions.
地板
發(fā)表于 2025-3-22 06:18:04 | 只看該作者
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發(fā)表于 2025-3-22 09:57:14 | 只看該作者
2038-5714 ntal the concept of random numbers.Includes numerous exercis.This?book provides an introduction to elementary probability?and to Bayesian statistics using?de Finetti‘s subjectivist approach. One of the features of this approach is that it does not require the?introduction of?sample space –?a non-int
6#
發(fā)表于 2025-3-22 16:51:00 | 只看該作者
Textbook 2016 of this approach is that it does not require the?introduction of?sample space –?a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate –?but introduces as fundamental the concept of random numbers directly related to their?interpretation in applications.
7#
發(fā)表于 2025-3-22 18:56:48 | 只看該作者
Random Numbersdom numbers. What is meant by .? A random number is a well defined number, whose value is not necessarily known. For example we can use random numbers to describe the result of a determined experiment, or the value of an option at a prefixed time, or the value of a meteorological magnitude at a give
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發(fā)表于 2025-3-22 23:33:30 | 只看該作者
https://doi.org/10.1007/978-3-319-07254-8Bayesian statistics; Conditional expectation; Logical dependence; Markov chains; Probability
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發(fā)表于 2025-3-23 04:48:51 | 只看該作者
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