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Graphical data analysis with R /

"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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Unwin, Antony (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton, FL : CRC Press, [2015]
Colección:Chapman & Hall/CRC the R series (CRC Press)
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Unwin, Antony,  |e author. 
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520 |a "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. Features: Concentrates on why graphics are drawn and what they reveal -- Emphasises the value of drawing a variety of different graphics -- Uses real datasets in R to show how graphical data analysis works in practice -- Supplies R code for all the graphics on the author's website -- Includes a set of exercises in each chapter to facilitate hands-on learning."--Back cover 
505 0 |a Setting the Scene -- Brief Review of the Literature and Background Materials -- Examining Continuous Variables -- Displaying Categorical Data -- Looking for Structure: Dependency Relationships and Associations -- Investigating Multivariate Continuous Data -- Studying Multivariate Categorical Data -- Getting an Overview -- Graphics and Data Quality: How Good Are the Data? -- Comparisons, Comparisons, Comparisons -- Graphics for Time Series -- Ensemble Graphics and Case Studies -- Some Notes on Graphics with R -- Summary. 
504 |a Includes bibliographical references. 
588 0 |a Online resource; title from title page (viewed May 6, 2016). 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Information visualization. 
650 0 |a Visual analytics. 
650 0 |a Data mining  |x Graphic methods. 
650 0 |a R (Computer program language) 
650 6 |a Visualisation de l'information. 
650 6 |a Analyse visuelle. 
650 6 |a Exploration de données (Informatique)  |x Méthodes graphiques. 
650 6 |a R (Langage de programmation) 
650 7 |a REFERENCE  |x Questions & Answers.  |2 bisacsh 
650 7 |a Information visualization.  |2 fast  |0 (OCoLC)fst00973185 
650 7 |a R (Computer program language)  |2 fast  |0 (OCoLC)fst01086207 
650 7 |a Visual analytics.  |2 fast  |0 (OCoLC)fst01743387 
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830 0 |a Chapman & Hall/CRC the R series (CRC Press) 
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