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32812792
Computational Statistics (Wiley Series in Computational Statistics)
82% of respondents would recommend this to a friend
Item #:
32812792
XPF 13299
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A comprehensive guide to modern and classical methods of statistical computing, now with updated coverage and new topics.
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What Stands Out
Comprehensive Coverage
Covers a wide range of computational techniques in statistics, providing readers with in-depth knowledge and practical applications in data analysis and statistical modeling.
Expert Contributions
Authored by leading experts in the field, ensuring high-quality content and insights that are both reliable and innovative for researchers and practitioners.
Applicable Tools
Includes practical tools and algorithms for real-world applications, equipping readers with essential skills to solve complex statistical problems effectively.
Product Details
| Publisher | Wiley |
| Publication date | November 6, 2012 |
| Edition | 2nd |
| Language | English |
| Print length | 496 pages |
| ISBN-10 | 9780470533314 |
| ISBN-13 | 978-0470533314 |
| Item Weight | 1.87 pounds (850 grams) |
| Dimensions | 6.3 x 0.9 x 9.2 inches (16 x 2.3 x 23.4 cm) |
Who Should Buy?
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Graduate Students
Ideal for graduate students specializing in statistics, providing thorough theoretical and practical computational methods.
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Data Scientists
Designed for data scientists seeking to enhance their statistical analysis skills with computational techniques and methodologies.
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Researchers
Beneficial for researchers looking to apply computational statistics in their work across various disciplines and projects.
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Beginners in Statistics
Not suitable for beginners due to its advanced content and requirement for prior statistical knowledge and experience.
Product Description
Computational Statistics (Wiley Series in Computational Statistics)
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Probability & Statistics Editorial Review
The Computational Statistics 2nd Edition is a traditional textbook that focuses on numerical methods for statistics. It is a decent resource for students pursuing a Masters degree in statistics, however, there are better options available for those interested in computation and modern statistics. The book may be of interest for its implementation of numerical methods, although some errors were found. Overall, it is recommended to consider alternatives and utilize online resources.
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Pros
- Provides implementation of numerical methods for statistics
Cons
- Not the best option for computation and modern statistics
Product Price History
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Features & Benefits
- Comprehensive guide covering modern and classical statistical computing methods.
- Includes detailed sections on Optimization, Integration, Simulation, Bootstrapping, and Density Estimation.
- Updated content with new topics such as adaptive MCMC and bootstrapping for correlated data.
- Step-by-step implementation summaries for key statistical methods.
- Access to comprehensive R code available on the book's website.
- Extensive exercises and real-world examples enhance practical application.
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