Description
Graphical Data Analysis with R
Chapman & Hall/CRC The R Series
Author: Unwin Antony
Language: EnglishSubjects for Graphical Data Analysis with R:
Keywords
Boston Housing Dataset; UCI Machine Learn Repository; Graphical data analysis; West Germany; Data visualisation; Parallel Coordinate Plots; R graphics; Vice Versa; Exploratory data analysis; Mass Package; Scatterplots; Trellis Plot; Histograms; Funnel Plot; Barcharts; Multivariate Categorical Data; Titanic Dataset; Mosaicplots; Trellis Graphics; Boxplots; Scatterplot Matrix; Bivariate Outlier; Swiss Banknotes; Scatterplot Matrices; Iris Dataset; Fluctuation Diagram; Default Histogram; Bank Dataset; Robust Mahalanobis Distance; Multiple Barcharts; Contrast Tukey; CSU Supporter; Hell Creek Formation; CSU Party
Publication date: 01-2023
· 15.6x23.4 cm · Paperback
Publication date: 05-2015
310 p. · 15.6x23.4 cm · Hardback
Description
/li>Contents
/li>Readership
/li>Biography
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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.
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. References. Indices.
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.