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257436220
Bayes' Rule With Python: A Tutorial Introduction to Bayesian Analysis, (Paperback)
Item #:
257436220
SAR 127
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This richly illustrated book uses accessible examples to show how Bayes' rule is a natural consequence of common sense reasoning.
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Product Details
- Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis. Note that this book includes Python (3.0) code snippets, which reproduce key numerical results and diagrams.
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Textbooks |
| Publication date | October, 2016 |
| Pages | 188 |
| Subgenre | Probability & Statistics |
| Series title | No Series |
| Edition | 1 |
| Publisher | Sebtel Press |
| Original languages | English |
| Language | English |
| Edu focus | Mathematics |
| Is collectible | N |
| Binding type | Perfect Binding |
| Retail packaging | Single Piece |
| Assembled product height | 9 in |
| Assembled product weight | 0.57 lb (260 grams) |
| Bisac subject heading | Mathematics |
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Dr James V Stone All Books Editorial Review
Bayes' Rule With Python: A Tutorial Introduction to Bayesian Analysis is a comprehensive guide for anyone eager to understand Bayesian analysis, blending theory with practical Python applications. This non-fiction textbook, first published in October 2016, spans 188 pages and focuses on the intricate world of probability and statistics. The perfect binding and compact format make it convenient for both students and practitioners. The text is presented in English, ensuring accessibility for a wide audience. Readers praise its clear explanations and practical coding examples, however, some may find the coverage of advanced topics lacking context for beginners.
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Pros
- Clear explanations of Bayesian concepts
- Practical coding examples in Python
- Well-structured for self-study
- Ideal for students and professionals
- Engaging textbook format
Cons
- May not cover advanced topics in depth
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Features & Benefits
- Comprehensive primer on Bayesian analysis for novices.
- Rich illustrations and intuitive examples enhance understanding.
- Includes Python (3.0) code snippets for practical application.
- Easy-to-follow tutorial style makes learning accessible.
- Emphasizes common sense reasoning in understanding Bayes' rule.
- Ideal for those looking to familiarize themselves with probability theory.
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