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1、Data Analysis and Graphics Using R, Third EditionDiscover 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 a
2、nalysis, 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 data sets, allowing readers to reproduce all analyses, along with solutions to selected exercises and
3、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 e
4、dition takes into account recent changes in R, including advances in graph- ical user interfaces (GUIs) and graphics packages. The treatments of the random forests methodology and one-way analysis have been extended. Both text and code have been revised throughout, and where possible simplified. New
5、 graphs and examples have been added.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
6、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, biolo- gists, psychologists, and most recently has become involved with a network o
7、f forestry researchers.Data Analysis and Graphics Using R an Example-Based ApproachThird EditionCAMBRIDGE SERIES IN STATISTICAL AND PROBABILISTIC MATHEMATICS Editorial BoardZ. Ghahramani (Department of Engineering, University of Cambridge)R. Gill (Mathematical Institute, Leiden University)F. P. Kell
8、y (Department of Pure Mathematics and Mathematical Statistics, University of Cambridge)B. D. Ripley (Department of Statistics, University of Oxford)S. Ross (Department of Industrial and Systems Engineering, University of Southern California)B. W. Silverman (St Peters College, Oxford)M. Stein (Depart
9、ment of Statistics, University of Chicago)This series of high quality upper-division textbooks and expository monographs covers all aspects of stochastic applicable mathematics. The topics range from pure and applied statistics to probability theory, operations research, optimization, and mathematic
10、al pro- gramming. The books contain clear presentations of new developments in the field and also of the state of the art in classical methods. While emphasizing rigorous treatment of theoretical methods, the books also contain applications and discussions of new techniques made possible by advances
11、 in computational practice.A complete list of books in the series can be found at http:/www.cambridge.org/uk/series/sSeries.asp?code=CSPM Recent titles include the following:7. Numerical Methods of Statistics, by John F. Monahan8. A Users Guide to Measure Theoretic Probability, by David Pollard9. Th
12、e Estimation and Tracking of Frequency, by B. G. Quinn and E. J. Hannan10. Data Analysis and Graphics Using R, by John Maindonald and John Braun11. Statistical Models, by A. C. Davison12. Semiparametric Regression, by David Ruppert, M. P. Wand and R. J. Carroll13. Exercises in Probability, by Loc Ch
13、aumont and Marc Yor14. Statistical Analysis of Stochastic Processes in Time, by J. K. Lindsey15. Measure Theory and Filtering, by Lakhdar Aggoun and Robert Elliott16. Essentials of Statistical Inference, by G. A. Young and R. L. Smith17. Elements of Distribution Theory, by Thomas A. Severini18. Stat
14、istical Mechanics of Disordered Systems, by Anton Bovier19. The Coordinate-Free Approach to Linear Models, by Michael J. Wichura20. Random Graph Dynamics, by Rick Durrett21. Networks, by Peter Whittle22. Saddlepoint Approximations with Applications, by Ronald W. Butler23. Applied Asymptotics, by A.
15、R. Brazzale, A. C. Davison and N. Reid24. Random Networks for Communication, by Massimo Franceschetti and Ronald Meester25. Design of Comparative Experiments, by R. A. Bailey26. Symmetry Studies, by Marlos A. G. Viana27. Model Selection and Model Averaging, by Gerda Claeskens and Nils Lid Hjort28. B
16、ayesian Nonparametrics, edited by Nils Lid Hjort et al29. From Finite Sample to Asymptotic Methods in Statistics, by Pranab K. Sen, Julio M. Singer and Antonio C. Pedrosa de Lima30. Brownian Motion, by Peter Morters and Yuval PeresData Analysis and Graphics Using R an Example-Based ApproachThird EditionJohn MaindonaldMathematical Sciences Institute, Australian Nat
