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Data Analysis and Graphics Using R 3rd Edition Hardback: An Example-Based Approach: 10 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10) - Hardcover
Inhaltsangabe
This third edition of the popular guide to using R reflects recent improvements to the R system, including major advances in graphical user interfaces and graphics packages. It emphasizes hands-on analysis, graphical display and interpretation of data. Ideal for researchers, students of applied statistics, and practising statisticians.
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Críticas
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.' 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.' 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.' 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.' 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.' DM Review Online
Biografía del autor
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.
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- VerlagCambridge University Press
- Erscheinungsdatum2010
- ISBN 10 0521762936
- ISBN 13 9780521762939
- EinbandTapa dura
- SpracheEnglisch
- Auflage3
- Anzahl der Seiten552
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Data Analysis and Graphics Using R
Verlag:
Cambridge University Press, 2010
ISBN 10: 0521762936
ISBN 13: 9780521762939
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Hardcover
Anbieter: ThriftBooks-Dallas, Dallas, TX, USA
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Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 2.9. Artikel-Nr. G0521762936I4N00
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Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
Verlag:
Cambridge University Press, 2010
ISBN 10: 0521762936
ISBN 13: 9780521762939
Gebraucht
Hardcover
Anbieter: Prior Books Ltd, Cheltenham, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Hardcover. Zustand: Like New. Third Edition. Hardback book in nearly new condition: firm and square with strong joints. Just a few hardly noticeable rubs or very mild bumps. Hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a very nice book in great condition, now offered for sale at a reasonable price. Artikel-Nr. 204439
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Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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Data Analysis and Graphics Using R
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Artikel-Nr. 9780521762939
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