1. Graphical data analysis with R [2015]
 Unwin, Antony, author.
 Boca Raton : CRC Press, Taylor & Francis Group, [2015]
 Description
 Book — xiii, 296 pages : illustrations (some color) ; 25 cm.
 Summary

 Setting the Scene Graphics in action Introduction What is graphical data analysis (GDA)? Using this book, the R code in it, and the book's webpage
 Brief Review of the Literature and Background Materials Literature review Interactive graphics Other graphics software Websites Datasets Statistical texts
 Examining Continuous Variables Introduction What features might continuous variables have? Looking for features Comparing distributions by subgroups What plots are there for individual continuous variables? Plot options Modelling and testing for continuous variables
 Displaying Categorical Data Introduction What features might categorical variables have? Nominal datano fixed category order Ordinal datafixed category order Discrete datacounts and integers Formats, factors, estimates, and barcharts Modelling and testing for categorical variables
 Looking for Structure: Dependency Relationships and Associations Introduction What features might be visible in scatterplots? Looking at pairs of continuous variables Adding models: lines and smooths Comparing groups within scatterplots Scatterplot matrices for looking at many pairs of variables Scatterplot options Modelling and testing for relationships between variables
 Investigating Multivariate Continuous Data Introduction What is a parallel coordinate plot (pcp)? Features you can see with parallel coordinate plots Interpreting clustering results Parallel coordinate plots and time series Parallel coordinate plots for indices Options for parallel coordinate plots Modelling and testing for multivariate continuous data Parallel coordinate plots and comparing model results
 Studying Multivariate Categorical Data Introduction Data on the sinking of the Titanic What is a mosaicplot? Different mosaicplots for different questions of interest Which mosaicplot is the right one? Additional options Modelling and testing for multivariate categorical data
 Getting an Overview Introduction Many individual displays Multivariate overviews Multivariate overviews for categorical variables Graphics by group Modelling and testing for overviews
 Graphics and Data Quality: How Good Are the Data? Introduction Missing values Outliers Modelling and testing for data quality
 Comparisons, Comparisons, Comparisons Introduction Making comparisons Making visual comparisons Comparing group effects graphically Comparing rates visually Graphics for comparing many subsets Graphics principles for comparisons Modelling and testing for comparisons
 Graphics for Time Series Introduction Graphics for a single time series Multiple series Special features of time series Alternative graphics for time series R classes and packages for time series Modelling and testing time series
 Ensemble Graphics and Case Studies Introduction What is an ensemble of graphics? Combining different viewsa case study example Case studies
 Some Notes on Graphics with R Graphics systems in R Loading datasets and packages for graphical analysis Graphics conventions in statistics What is a graphic anyway? Options for all graphics Some R graphics advice and coding tips Other graphics Large datasets Perfecting graphics
 Summary Data analysis and graphics Key features of GDA Strengths and weaknesses of GDA Recommendations for GDA
 References General Index Datasets Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
QA76.9 .I52 U59 2015  Unknown 