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Graphics for statistics and data analysis with R

Author: K J Keen
Publisher: Boca Raton, FL : CRC Press, [2018]
Series: Chapman & Hall/CRC Texts in Statistical Science
Edition/Format:   eBook : Document : English : Second editionView all editions and formats
Summary:
"Praise for the First Edition"The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion of R code is particularly useful to assist readers understanding of the graphical techniques discussed in the book. It not only summarises  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Keen, Kevin J.
Graphics for statistics and data analysis with R
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: K J Keen
ISBN: 9781351007726 1351007726 9781351007702 135100770X
OCLC Number: 1027755972
Description: 1 online resource
Contents: Intro; Halftitle Page; Title Page; Copyright; Table of Contents; Preface to the First Edition; Preface to the Second Edition; Acknowledgments; Part I Introduction; 1 The Graphical Display of Information; 1.1 Introduction; 1.2 Learning Outcomes; 1.3 Know the Intended Audience; 1.4 Principles of Effective Statistical Graphs; 1.4.1 The Layout of a Graphical Display; 1.4.2 The Design of Graphical Displays; 1.5 Graphicacy; 1.6 The Grammar of Graphics; 1.7 Graphical Statistics; 1.8 Conclusion; 1.9 Exercises; Part II A Single Discrete Variable 2 Basic Charts for the Distribution of a Single Discrete Variable2.1 Introduction; 2.2 Learning Outcomes; 2.3 An Example from the United Nations; 2.4 The Dot Chart; 2.5 The Bar Chart; 2.5.1 Definition; 2.5.2 Pseudo-Three-Dimensional Bar Chart; 2.6 The Pie Chart; 2.6.1 Definition; 2.6.2 Pseudo-Three-Dimensional Pie Chart; 2.6.3 Recommendations Concerning the Pie Chart; 2.7 Conclusion; 2.8 Exercises; 3 Advanced Charts for the Distribution of a Single Discrete Variable; 3.1 Introduction; 3.2 Learning Outcomes; 3.3 The Stacked Bar Chart; 3.3.1 Definition 3.3.2 The Stacked Bar Plot versus the Bar Chart and the Pie Chart3.4 The Pictograph; 3.4.1 Definition; 3.4.2 The Pictograph versus the Dot Chart and the Bar Chart; 3.5 Variations on the Dot and Bar Charts; 3.5.1 The Bar-Whisker Chart; 3.5.2 Dot-Whisker Chart; 3.6 Frames, Grid Lines, and Order; 3.6.1 Frame; 3.6.2 Grid Lines; 3.6.3 Order; 3.7 Conclusion; 3.8 Exercises; Part III A Single Continuous Variable; 4 Exploratory Plots for the Distribution of a Single Continuous Variable; 4.1 Introduction; 4.2 Learning Outcomes; 4.3 The Dotplot; 4.3.1 Definition; 4.3.2 Variations on the Dotplot 4.4 The Stemplot4.4.1 Definition; 4.5 The Boxplot; 4.5.1 Definition; 4.5.2 Variations on the Boxplot; 4.6 The EDF Plot; 4.6.1 Definition; 4.6.2 The EDF Plot as a Diagnostic Tool; 4.7 Conclusion; 4.8 Exercises; 5 Diagnostic Plots for the Distribution of a Continuous Variable; 5.1 Introduction; 5.2 Learning Outcomes; 5.3 The Quantile-Quantile Plot; 5.4 The Probability Plot; 5.5 Estimation of Quartiles and Percentiles*; 5.5.1 Estimation of Quartiles; 5.5.2 Estimation of Percentiles; 5.6 Conclusion; 5.7 Exercises; 6 Nonparametric Density Estimation for a Single Continuous Variable 6.1 Introduction6.2 Learning Outcomes; 6.3 The Histogram; 6.3.1 Definition; 6.3.2 A Circular Variation on the Histogram: The Rose Diagram; 6.4 Kernel Density Estimation; 6.5 Spline Density Estimation∗; 6.6 Choosing a Plot for a Continuous Variable; 6.7 Conclusion; 6.8 Exercises; 7 Parametric Density Estimation for a Single Continuous Variable; 7.1 Introduction; 7.2 Learning Outcomes; 7.3 Normal Density Estimation; 7.4 Transformations to Normality; 7.5 Pearson's Curves; 7.6 Gram-Charlier Series Expansion; 7.7 Conclusion; 7.8 Exercises; Part IV Two Variables
Series Title: Chapman & Hall/CRC Texts in Statistical Science
Responsibility: Kevin J. Keen.

Abstract:

"Praise for the First Edition"The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion of R code is particularly useful to assist readers understanding of the graphical techniques discussed in the book. It not only summarises graphical techniques, but it also serves as a practical reference for researchers and graduate students with an interest in data display."--Han Lin Shang,?Journal of Applied StatisticsGraphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles of graphical design and applies these principles to engaging examples using the graphics and lattice packages in R. It offers a wide array of modern graphical displays for data visualization and representation. Added in the second edition are coverage of the ggplot2 graphics package, material on human visualization and color rendering in R, on screen, and in print. FeaturesEmphasizes the fundamentals of statistical graphics and best practice guidelines for producing and choosing among graphical displays in RPresents technical details on topics such as: the estimation of quantiles, nonparametric and parametric density estimation; diagnostic plots for the simple linear regression model; polynomial regression, splines, and locally weighted polynomial regression for producing a smooth curve; Trellis graphics for multivariate dataProvides downloadable R code and data for figures at www.graphicsforstatistics.comKevin J. Keen is a Professor of Mathematics and Statistics at the University of Northern British Columbia (Prince George, Canada) and an Accredited Professional StatisticianTM by the Statistical Society of Canada and the American Statistical Association."--Provided by publisher.

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