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artikal br.:
16393256
A First Course in Bayesian Statistical Methods Springer Texts in Statistics 2009th Edition
artikal br.:
16393256
RSD 6123
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What Stands Out
Comprehensive Coverage
Offers a thorough introduction to Bayesian statistical methods, making complex concepts accessible for beginners and acting as a solid foundation for further study.
Practical Applications
Includes real-world examples and exercises that enhance understanding, allowing readers to apply Bayesian methods in practical scenarios and improve problem-solving skills.
Authoritative Source
Written by experts in the field, this text ensures high-quality content and credibility, making it an essential resource for students and professionals in statistics.
Детаљи о производу
| Publisher | Springer |
| Publication date | June 15, 2009 |
| Edition | 2009th |
| Language | English |
| Print length | 280 pages |
| ISBN-10 | 0387922997 |
| ISBN-13 | 978-0387922997 |
| Item Weight | 2.8 pounds (1.27 kg) |
| Dimensions | 6.14 x 0.69 x 9.21 inches (15.6 x 1.8 x 23.4 cm) |
| Part of series | Springer Texts in Statistics |
Who Should Buy?
-
Beginner Statisticians
Ideal for those new to statistics, providing a clear introduction to Bayesian concepts and methods.
-
Graduate Students
Suitable for graduate-level coursework, as it covers essential Bayesian methodologies comprehensively.
-
Data Scientists
Beneficial for data professionals seeking to apply Bayesian techniques in statistical modeling and data analysis.
-
Casual Readers
Not ideal for casual readers lacking a statistical background, as the content may be too technical.
OPIS PROIZVODA
A First Course in Bayesian Statistical Methods Springer Texts in Statistics 2009th Edition
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Probability & Statistics Editorial Review
A First Course in Bayesian Statistical Methods is a highly recommended book for those interested in learning about the Bayesian framework. It provides a deep understanding of Bayesian procedure concepts without requiring advanced mathematical knowledge. The book is thorough and well-motivated with helpful applications and figures. One drawback is the presence of some minor typos, although the author provides a list of them on the book's webpage. Overall, this book is an excellent resource for learners of Bayesian statistics.
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- Suitable for a wide range of people
- Provides a deep understanding of Bayesian procedure concepts
- R code for figures available on author's webpage
- Thorough and well-motivated with helpful applications and figures
- Good resource for learners of Bayesian statistics
Цонс
- Presence of some minor typos
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