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Graphics for Statistics and Data Analysis with R
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Graphics for Statistics and Data Analysis with R

Book Details

Format Hardback or Cased Book
ISBN-10 1498779832
ISBN-13 9781498779838
Publisher Taylor & Francis Inc
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date May 18th, 2018
Print length 610 Pages
Weight 1,138 grams
Dimensions 17.10 x 23.60 x 3.90 cms
Ksh 16,550.00
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The book presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide variety of graphical displays for the presentation of data, including modern tools for data visualization and representation. The second edition will add examples with the R package ggplot2 in addition to examples with the base and lattice packages in the first edition.

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 Statistics

Graphics 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.

Features

  • Emphasizes the fundamentals of statistical graphics and best practice guidelines for producing and choosing among graphical displays in R
  • Presents 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 data
  • Provides downloadable R code and data for figures at www.graphicsforstatistics.com

Kevin 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.


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