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R in a Nutshell
R in a Nutshell
★★★★★
★★★★★
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€59.99
A01=Joseph Adler
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Author_Joseph Adler
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r data statistics informatics graphics visualization analysis data analysis data visualization data modelling analysis of variance variance
softlaunch
Product details
- ISBN 9781449312084
- Publication Date: 13 Nov 2012
- Publisher: O'Reilly Media
- Publication City/Country: US
- Product Form: Paperback
- Language: English
Delivery/Collection within 10-20 working days
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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
Joseph Adler has years of experience working with lots of popular data mining packages, including databases (including Oracle, PostgreSQL, and MS Access), statistical analysis tools (SAS, SPSS, S-Plus, and R), and data mining tools (SAS Enterprise Miner, Insightful Miner, Oracle Data Mining, Weka, and SPSS Clementine). He is currently leading a project at Verisign to pick a data mining package for enterprise deployment.
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