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Item #:
30708971
Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
85% of respondents would recommend this to a friend
Item #:
30708971
AUD 119
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Discover what you can do with R! This book guides users through practical, powerful tools for hands-on analysis and interpretation of data.
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What Stands Out
Example-Based Learning
Offers practical, example-driven learning that makes complex concepts accessible, enhancing understanding and retention for students and professionals alike.
Comprehensive Coverage
Thoroughly covers data analysis techniques and graphics using R, equipping readers with essential skills needed for real-world data scenarios and problem-solving.
Updated Content
Includes the latest advancements in R and statistical methods, ensuring readers stay current in the rapidly evolving field of data science.
Product Details
- Discover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practicing statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.
| Publisher | Cambridge University Press |
| Publication date | June 7, 2010 |
| Edition | 3rd |
| Language | English |
| Print length | 549 pages |
| ISBN-10 | 0521762936 |
| ISBN-13 | 978-0521762939 |
| Item Weight | 2.87 pounds (1.3 kg) |
| Dimensions | 7.25 x 1.25 x 10 inches (18.4 x 3.2 x 25.4 cm) |
| Part of series | Cambridge Series in Statistical and Probabilistic Mathematics |
Who Should Buy?
-
Students and Learners
Perfect for students aiming to solidify their understanding of data analysis using R through practical examples.
-
Data Analysts
Ideal for professionals who need to enhance their data visualization skills and apply statistical techniques effectively.
-
Teachers and Educators
Beneficial for educators looking for comprehensive teaching materials and examples to guide students in data analysis.
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Complete Beginners
Not suitable for individuals with no prior experience in R or data analysis concepts, as it assumes some knowledge.
Product Description
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Customer Questions & Answers
-
Question:
Who is this book ideal for?
Answer: It's ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practicing statisticians. -
Question:
Does the book require prior knowledge of R?
Answer: No, it assumes basic statistical knowledge and some experience with data analysis, but not prior experience with R. -
Question:
What additional resources come with the book?
Answer: A companion website offers code, datasets, and solutions to selected exercises to enhance learning and reproducibility. -
Question:
Is this book helpful for learning R?
Answer: Yes, this book is very useful for learning R and provides code examples and highlights common pitfalls for new users.
Biostatistics Editorial Review
This book is highly recommended for anyone looking to learn R and statistics. It provides useful code examples and highlights common pitfalls for new users. The included website allows for easy access to downloadable code. While there are free resources available, this hard-bound reference book offers a comprehensive and organized approach to learning R. It covers a range of statistical applications and provides value even if only a few chapters are utilized.
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Pros
- Useful for learning R
- Includes code examples
- Highlights common pitfalls
- Comprehensive reference
- Covers range of statistical applications
Cons
- Not focused solely on statistics
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AUD 119
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Features & Benefits
- Learn practical and powerful tools of R for data analysis.
- Hands-on approach with real-world examples and detailed commentary.
- Covers standard regression methods and advanced topics.
- Companion website with code and datasets for reproducibility.
- Perfect for researchers, students of applied statistics, and practicing statisticians.
- Expanded content on Bayesian inference, mixed models, and random forests.
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