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Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10) 3rd Edition by John Maindonald (Author), W. John Braun (Author)

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Language‏:‎English

Hardcover‏:‎549pages

ISBN-10‏:‎0521762936

ISBN-13‏:‎978-0521762939

Categories: ,

Description

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. Read more

Review “I would strongly recommend the book to scientists who have already had a regression or a linear models course and who wish to learn to use R. I give it a strong recommendation to the scientist or data analyst who wishes to an easy-to-read and an understandable reference on the use of R for practical data analysis.” R News”The style of the book is a commendable “learn by example” – each of the many statistical techniques is centered on real-world examples. The collective of topics is eclectic and the book also comes with extensive R code.” Carl James Schwarz, Biometrics Book Description Hands-on guide to the R system for data analysis for scientists, students and practising statisticians. About the Author John Maindonald is Visiting Fellow at the Mathematical Sciences Institute at the Australian National University. He has collaborated extensively with scientists in a wide range of application areas, from medicine and public health to population genetics, machine learning, economic history, and forensic linguistics.W. John Braun is Professor in the Department of Statistical and Actuarial Sciences at the University of Western Ontario. He has collaborated with biostatisticians, biologists, psychologists, and most recently has become involved with a network of forestry researchers. Read more

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