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Graphical data analysis with R

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서명/저자사항Graphical data analysis with R/ Antony Unwin.
개인저자Unwin, Antony,author.
형태사항1 online resource (1 volume): illustrations.
총서사항Chapman & Hall/CRC the R series
기타형태 저록Original 9781498715232 1498715230
ISBN9781498715249
1498715249




서지주기Includes bibliographical references.
내용주기Setting 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.
요약"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.
일반주제명Information visualization.
Visual analytics.
Data mining --Graphic methods.
R (Computer program language)
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