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Graphical Data Analysis with R

Antony Unwin (University of Augsburg)

$152

Hardback

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English
Chapman & Hall/CRC
20 May 2015
See How Graphics Reveal Information

Graphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages and the R code is available at rosuda.org/GDA.

Graphical data analysis is useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modelling output, and presenting results. This book guides you in choosing graphics and understanding what information you can glean from them. It can be used as a primary text in a graphical data analysis course or as a supplement in a statistics course. Colour graphics are used throughout.

By:  
Imprint:   Chapman & Hall/CRC
Country of Publication:   United States
Dimensions:   Height: 234mm,  Width: 156mm,  Spine: 18mm
Weight:   650g
ISBN:   9781498715232
ISBN 10:   1498715230
Series:   Chapman & Hall/CRC The R Series
Pages:   312
Publication Date:  
Audience:   Professional and scholarly ,  College/higher education ,  Undergraduate ,  Primary
Format:   Hardback
Publisher's Status:   Active

Antony Unwin is a professor of computer-oriented statistics and data analysis at the University of Augsburg. He is a fellow of the American Statistical Society, co-author of Graphics of Large Datasets, and co-editor of the Handbook of Data Visualization. His research focuses on data visualisation, especially in interactive graphics. His research group has developed several pieces of interactive graphics software and written packages for R.

Reviews for Graphical Data Analysis with R

Overall, the book is a very good introduction to the practical side of graphical data analysis using R. The presentation of R code and graphics output is excellent, with colours used when required. The book appears to be free of typographical and other errors, and its index is useful. Also, the book is well written and neatly structured. I enjoyed reading the book and can recommend it to anyone who wants to learn more about their data through graphics using R. It will also be a valuable asset for a library and as part of an undergraduate course in applied statistics. (Journal of the Royal Statistical Society, Series A) ... an attractive addition to the current statistical graphics texts as it demonstrates what can be learned through graphs. -Significance Magazine, February 2016 ... the strength of this book lies in the profound introduction to the topic of graphical data analysis. The comprehensive sectional introductions and overviews along with the 'how-to' might well be regarded as the modern update to Tukey's 1977 landmark book. -Biometrical Journal, December 2015 Antony Unwin's very clever new book ... is well written, clearly by a practitioner with wide experience, gives generally good (though sometimes opinionated) advice, and includes R code for nearly all examples, as well as nice collections of additional exercises for each chapter ... Beyond the content, Unwin also does an admirable job of conveying enthusiasm for data graphics. -Journal of Educational and Behavioral Statistics, December 2015 This text has the potential of bringing sophisticated visualization to a broad audience without resorting to mathematical formalizations or the skills of a graphics artist. It engages the reader with interesting graphics right from the start and overall is clear and unintimidating. Code for all examples is provided in the text and is available on a supporting website. What's more, the code works as is, rather unusual and refreshing. -Journal of Statistical Software, November 2015 For statisticians and experts in data analysis, the book is without doubt the new reference work on the subject. -Thomas Rahlf, datendesign-r.de ...would also be an excellent suggested additional reading for a pragmatic graphical data analysis-oriented course. -Reijo Sund, Centre for Research Methods, University of Helsinki


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