소장자료
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020 | ▼a9780521762939▲ | ||
020 | ▼a0521762936▲ | ||
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050 | 0 | 0 | ▼aQA276.4▼b.M245 2010▲ |
082 | 0 | 0 | ▼a519.50285▼221▲ |
090 | ▼a519.50285▼bM224d3▲ | ||
100 | 1 | ▼aMaindonald, J. H.▼q(John Hilary),▼d1937-▲ | |
245 | 1 | 0 | ▼aData analysis and graphics using R :▼ban example-based approach /▼cJohn Maindonald and W. John Braun.▲ |
250 | ▼a3rd ed.▲ | ||
260 | ▼aCambridge ;▼aNew York :▼bCambridge University Press,▼c2010.▲ | ||
300 | ▼axxvi, 525 p., [12] p. of plates :▼bill. (some col.) ;▼c27 cm.▲ | ||
490 | 0 | ▼aCambridge series in statistical and probabilistic mathematics ;▼v10▲ | |
504 | ▼aIncludes bibliographical references and indexes.▲ | ||
505 | 0 | ▼aA brief introduction to R -- Styles of data analysis -- Statistical models -- A review of inference concepts -- Regression with a single predictor -- Multiple linear regression -- Exploiting the linear model framework -- Generalized linear models and survival analysis -- Time series models -- Multi-level models, and repeated measures -- Tree-based classification and regression -- Multivariate data exploration and discrimination -- Regression on principal component or discriminant scores -- The R system: additional topics -- Graphs in R.▲ | |
520 | ▼a"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"--Provided by publisher.▲ | ||
650 | 0 | ▼aStatistics▼xData processing.▲ | |
650 | 0 | ▼aStatistics▼xGraphic methods▼xData processing.▲ | |
650 | 0 | ▼aR (Computer program language)▲ | |
700 | 1 | ▼aBraun, John,▼d1963-▲ | |
830 | 0 | ▼aCambridge series on statistical and probabilistic mathematics ;▼v10.▲ | |
999 | ▼c정영주▲ |
Data analysis and graphics using R :an example-based approach
자료유형
국외단행본
서명/책임사항
Data analysis and graphics using R : an example-based approach / John Maindonald and W. John Braun.
개인저자
판사항
3rd ed.
발행사항
Cambridge ; New York : Cambridge University Press , 2010.
형태사항
xxvi, 525 p., [12] p. of plates : ill. (some col.) ; 27 cm.
총서사항
서지주기
Includes bibliographical references and indexes.
내용주기
A brief introduction to R -- Styles of data analysis -- Statistical models -- A review of inference concepts -- Regression with a single predictor -- Multiple linear regression -- Exploiting the linear model framework -- Generalized linear models and survival analysis -- Time series models -- Multi-level models, and repeated measures -- Tree-based classification and regression -- Multivariate data exploration and discrimination -- Regression on principal component or discriminant scores -- The R system: additional topics -- Graphs in R.
요약주기
"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"--Provided by publisher.
주제
ISBN
9780521762939 0521762936
청구기호
519.50285 M224d3
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