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  3. Data Analysis and Graphics Using R
  • Cited by 87
Publisher:
Cambridge University Press
Online publication date:
October 2013
Print publication year:
2010
Online ISBN:
9781139194648
DOI:
https://doi.org/10.1017/CBO9781139194648
Series:
Cambridge Series in Statistical and Probabilistic Mathematics (10)
Subjects:
Computational Statistics, Machine Learning and Information Science, General Statistics and Probability, Statistics and Probability
Information

Book 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 practising 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.

Reviews

From reviews of previous edition:‘The strength of the book is in the extensive examples of practical data analysis with complete examples of the R code necessary to carry out the analyses … 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 have an easy-to-read and an understandable reference on the use of R for practical data analysis.’

Source: R News

From reviews of previous edition:‘This book does an excellent job of describing the basics of a variety of statistical tools, both classical and modern, through examples from a wide variety of disciplines … the book’s writing style is very readable, with clear explanations and precise introductions of all topics and terminology … the book also provides a wealth of examples from various physical and social sciences, engineering, and medicine that have been effectively chosen to illustrate not only the basics of the statistical methods, but also some of the interesting subtleties of the analyses that may require careful interpretation and discussion … I believe that they have … created a readable book that is rich with clear explanations and illustrative examples of the capability of a diverse set of tools. The packaging of the material with the R language is natural, and the extensive web pages of resources complement the book’s usefulness for a road audience of statisticians and practitioners.’

Source: Biometrics

From reviews of previous edition:'This book does an excellent job of describing the basics of a variety of statistical tools, both classical and modern, through examples from a wide variety of disciplines … With its focus on ideas and concepts, rather than an extensive formula-based presentation, the book finds a nice balance between discussing statistical concepts and teaching the basics of the freely-available statistical package R … a readable book that is rich with clear explanations and illustrative examples of the capability of a diverse set of tools. The packaging of the material with the R language is natural, and the extensive web pages of resources complement the book's usefulness for a broad audience of statisticians and practitioners.'

Source: Journal of the American Statistical Association

From reviews of previous edition:‘... a very useful book that can be recommended for applied statisticians and other scientists who want to use R for data analysis, and as a textbook for an applied statistics course using R.’

Source: Journal of Applied Statistics

From reviews of previous edition:‘... an excellent intermediate-level text ... Though a bit more terse than Dalgaard's Introductory Statistics with R, Maindonald and Braun's exposition of the R language is nonetheless first rate.’

Source: DM Review Online

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