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Kunio Takezawa, "Guidebook to R Graphics Using Microsoft Windows"
English | 2012 | ISBN: 111802639X | 278 pages | PDF | 5 MB

Introduces the graphical capabilities of R to readers new to the software
Due to its flexibility & availability, R has become the computing software of choice for statistical computing & generating graphics across various fields of research.
Guidebook to R Graphics Using Microsoft® Windows offers a unique presentation of R, guiding new users through its many benefits, including the creation of high-quality graphics.

Beginning with getting the program up & running, this book takes readers step by step through the process of creating histograms, boxDescriptions, strip charts, time series graphs, steam-&-leaf displays, scatterDescription matrices, & map graphs. In addition, the book presents:

* Tips for establishing, saving, & printing graphs along with essential base-package Descriptionting functions
* Interactive R programs for carrying out common tasks such as inputting values, moving data on a natural spline, adjusting three-dimensional graphs, & underst&ing simple & local linear regression
* Various external packages for R that help to create more complex graphics like rimage, gDescriptions, ggDescription2, tripack, rworldmap, & Descriptionrix packages
Throughout the book, concise explanations of key concepts of R graphics assist readers in carrying out the presented procedures, & any coverage of functions is clearly written out & displayed in the text as demos. The discussed techniques are accompanied by a wealth of screenshots & graphics with related R code available on the book's FTP site, & numerous exercises allow readers to test their underst&ing of the presented material.
Guidebook to R Graphics Using Microsoft® Windows is a valuable resource for researchers in the fields of statistics, public health, business, & the life & social sciences who use or would like to learn how to use R to create visual representations of data. The book can also be used as a supplement for courses on statistical analysis at the upper-undergraduate level.
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