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An Introductory Handbook of Bayesian Thinking
Stephen C. Loftus
出版Elsevier, 2024-04-17
主題Mathematics / Probability & Statistics / General
ISBN044329111X9780443291111
URLhttp://books.google.com.hk/books?id=iukCEQAAQBAJ&hl=&source=gbs_api
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註釋An Introductory Handbook of Bayesian Thinking brings Bayesian thinking and methods to a wide audience beyond the mathematical sciences. Appropriate for students with some background in calculus and introductory statistics, particularly for nonstatisticians with a sufficient mathematical background, the text provides a gentle introduction to Bayesian ideas with a wide array of supporting examples from a variety of fields.
  • Utilizes real datasets to illustrate Bayesian models and their results
  • Guides readers on coding Bayesian models using the statistical software R, including a helpful introduction and supporting online resource
  • Appropriate for an undergraduate statistics course, as well as for non-statisticians with sufficient mathematical background (integral and differential Calculus and an introductory Statistics course)
  • Covers any more advanced topics which readers may not be familiar with, such as the basic idea of vectors and matrices