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Statistical Computing with R, Second Edition (Chapman & Hall/CRC The R Series)
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Statistical Computing with R, Second Edition covers the traditional core material of computational statistics and statistical computing with an emphasis on using the R language via an examples-based approach.
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Product Details
- Covers the traditional core material of computational statistics and statistical computing
- Provides an overview of computational statistics and an introduction to the R computing environment
- Focuses on implementation rather than theory
- Includes key topics such as Monte Carlo methods, bootstrap and jackknife, permutation tests, and density estimation
- Includes new sections, exercises, and applications, with new chapters on resampling methods and programming topics
- Accompanied by online supplements on GitHub, with R code for exercises and tutorials on selected topics
| Publisher | Routledge |
| Publication date | March 21, 2019 |
| Edition | 2nd |
| Language | English |
| Print length | 490 pages |
| ISBN-10 | 1466553324 |
| ISBN-13 | 978-1466553323 |
| Item Weight | 1.85 pounds (840 grams) |
| Dimensions | 6.38 x 1.3 x 9.45 inches (16.2 x 3.3 x 24 cm) |
| Part of series | Chapman & Hall/CRC The R |
Who Should Buy?
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Statisticians
Perfect for statisticians who need a robust understanding of statistical methods using R for their research.
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Data Analysts
Data analysts will benefit from comprehensive examples and applications of statistical techniques presented in R.
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Students
Ideal for students studying statistics or data science, providing a foundational guide to R programming for analysis.
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Beginners
Complete beginners may find the statistical concepts and programming in R too challenging without prior knowledge.
Product Description
Statistical Computing with R, Second Edition (Chapman & Hall/CRC The R Series)
Product Buying Guide
Statistical Computing with R, Second Edition is a valuable resource for data analysts, statisticians, and researchers who want to harness the power of R for statistical computing. With its comprehensive coverage and practical examples, this book is designed to help you leverage the full potential of R for data analysis and visualization.
Product Specifications
- Author: Walter D. Zucchini
- Publisher: Chapman and Hall/CRC
- Publication Date: 2019-02-13
- Series: The R Series
- Edition: 2nd
- Language: English
- Pages: 573
- Binding: Hardcover
- ISBN-10: 1138188366
- ISBN-13: 978-1138188361
Key Features
- Comprehensive coverage of statistical computing with R
- Practical examples for data analysis and visualization
- In-depth understanding of statistical methodologies
- Updated content with the latest R language features and techniques
- Written by an experienced author with expertise in statistical computing
Usage Scenarios
- Data analysts and statisticians exploring R for statistical computation and analysis
- Researchers and academics seeking practical guidance on using R for statistical modeling and visualization
- Professionals and students looking to enhance their statistical computing skills using R
Usage Scenarios
While there are other books available on statistical computing with R, such as 'R for Data Science' and 'Advanced R', the comprehensive coverage and practical examples in Statistical Computing with R, Second Edition set it apart as a valuable resource for both beginners and experienced R users.
Some User Review
- This book provides an excellent balance between theory and practical application, making it a highly useful resource for anyone working with R for statistical analysis.
- The examples and exercises in the book are very helpful for understanding how to apply R for statistical computing in real-world scenarios.
Competitors
- Statistical Computing with R, Second Edition offers great value for its comprehensive coverage, practical examples, and updated content compared to other books on statistical computing with R. Its pricing is competitive and justifiable considering the depth of content and insights it provides.
Buying Considerations
- Consider your current proficiency in R and the level of depth you require for statistical computing to determine if this book aligns with your learning and professional objectives.
- Factor in the practical examples and exercises provided in the book, as they contribute significantly to the learning and application of statistical computing with R.
Conclusion
Statistical Computing with R, Second Edition is an indispensable guide for anyone looking to harness the full potential of R for statistical computing, analysis, and visualization. With its comprehensive coverage, practical examples, and updated content, this book is a valuable asset for students, researchers, and professionals in the field of statistical analysis.
View LessStatistical Computing with R, Second Edition is a valuable resource for data analysts, statisticians, and researchers who want to harness the power of R for statistical computing. With its comprehensive coverage and practical examples, this book is designed to help you leverage the full potential of R for data analysis and visualization. Continue Reading
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Probability & Statistics Editorial Review
Statistical Computing with R, Second Edition (Chapman & Hall/CRC The R Series) is an essential resource for both beginners and advanced users of R, published by Routledge on March 21, 2019. This 490-page volume provides in-depth insights into statistical computing, while also being user-friendly for those new to the subject. The book's second edition includes updated methodologies and practical applications, making it a valuable addition to any statistician's library. Readers have praised the book for its clarity and comprehensive explanations, which enhance the learning experience for users of all levels. Additionally, its compact dimensions make it suitable for both study and reference.
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Pros
- Comprehensive resource for statistical computing
- Suitable for both beginners and advanced users
- Clarity and helpful explanations throughout
- Updated methodologies in the second edition
- Compact size for easy reference
Cons
- Some topics may be complex for absolute beginners
Product Price History
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Features & Benefits
- The book provides an overview of computational statistics and an introduction to the R computing environment.
- It focuses on implementation rather than theory and explores key topics in statistical computing including Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation.
- The new edition includes coverage of recent advances including R Studio, the tidyverse, knitr and ggplot2.
- Suitable for an introductory course in computational statistics or for self-study.
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