Book Details
Format
Paperback / Softback
ISBN-10
144931208X
ISBN-13
9781449312084
Edition
2 Revised edition
Publisher
O'Reilly Media
Imprint
O'Reilly Media
Country of Manufacture
US
Country of Publication
GB
Publication Date
Nov 13th, 2012
Print length
724 Pages
Weight
976 grams
Dimensions
22.90 x 15.40 x 3.80 cms
Product Classification:
Mathematical & statistical softwareMathematical and statistical software
Ksh 9,900.00
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R is rapidly becoming the standard for developing statistical software, and R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment.
Why learn R? Because it's rapidly becoming the standard for developing statistical software. R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics. The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems. * Understand the basics of the language, including the nature of R objects * Learn how to write R functions and build your own packages * Work with data through visualization, statistical analysis, and other methods * Explore the wealth of packages contributed by the R community * Become familiar with the lattice graphics package for high-level data visualization * Learn about bioinformatics packages provided by Bioconductor "I am excited about this book.R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians." --Martin Schultz, Arthur K. Watson Professor of Computer Science, Yale University
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