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Beginning R: An Introduction to Statistical Programming
Beginning R, Second Edition is a hands-on book showing howto use the R language, write and save R scripts, read in data files, and writecustom statistical functions as well as use built in functions. This book showsthe use of R in specific cases such as one-way ANOVA analysis, linear andlogistic regression, data visualization, parallel processing, bootstrapping,and more. It takes a hands-on, example-based approach incorporating bestpractices with clear explanations of the statistics being done. It has beencompletely re-written since the first edition to make use of the latestpackages and features in R version 3.
R is a powerful open-source language and programmingenvironment for statistics and has become the de facto standard for doing,teaching, and learning computational statistics. R is both an object-oriented language and afunctional language that is easy to learn, easy to use, and completely free. Alarge community of dedicated R users and programmers provides an excellentsource of R code, functions, and data sets, with a constantly evolvingecosystem of packages providing new functionality for data analysis. R has alsobecome popular in commercial use at companies such as Microsoft, Google, andOracle. Your investment in learning R is sure to pay off in the long term as Rcontinues to grow into the go to language for data analysis and research.
What You Will
How to acquire and install RHot to import and export data and scriptsHow to analyze data and generate graphicsHow to program in R to write custom functionsHot to use R for interactive statistical explorationsHow to conduct bootstrapping and other advancedtechniques
R is a powerful open-source language and programmingenvironment for statistics and has become the de facto standard for doing,teaching, and learning computational statistics. R is both an object-oriented language and afunctional language that is easy to learn, easy to use, and completely free. Alarge community of dedicated R users and programmers provides an excellentsource of R code, functions, and data sets, with a constantly evolvingecosystem of packages providing new functionality for data analysis. R has alsobecome popular in commercial use at companies such as Microsoft, Google, andOracle. Your investment in learning R is sure to pay off in the long term as Rcontinues to grow into the go to language for data analysis and research.
What You Will
How to acquire and install RHot to import and export data and scriptsHow to analyze data and generate graphicsHow to program in R to write custom functionsHot to use R for interactive statistical explorationsHow to conduct bootstrapping and other advancedtechniques
- GenresProgramming
753 pages, Kindle Edition
First published September 26, 2012
7 people are currently reading
27 people want to read
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Displaying 1 - 3 of 3 reviews
February 10, 2016
R is rightly acknowledged to be an open-source language and programming environment with accompanying online help, therefore any book has to be able to add value beyond what is already freely available.
This book is both well structured and written, supported by clear examples and supplementary material. It is highly recommended as a teaching resource, its chapter on Input and Output is particularly useful and comprehensively explained.
The only negative seems rather petty - some of the text, font and size could be an issue for some readers. Whilst content is always more important than presentation, in this case the latter could be improved.
Overall, this is an excellent book for students and practitioners, or individuals with an interest in a related topic, such as information visualisation and big data analytics.
Priced at $39.99 the paperback also represents good value for money.
Review by Deryn Graham FBCS, Senior Lecturer
Originally posted: http://www.bcs.org/content/conWebDoc/...
This book is both well structured and written, supported by clear examples and supplementary material. It is highly recommended as a teaching resource, its chapter on Input and Output is particularly useful and comprehensively explained.
The only negative seems rather petty - some of the text, font and size could be an issue for some readers. Whilst content is always more important than presentation, in this case the latter could be improved.
Overall, this is an excellent book for students and practitioners, or individuals with an interest in a related topic, such as information visualisation and big data analytics.
Priced at $39.99 the paperback also represents good value for money.
Review by Deryn Graham FBCS, Senior Lecturer
Originally posted: http://www.bcs.org/content/conWebDoc/...
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October 14, 2016Location: ND6 IRC
Accession No: DL028553
Accession No: DL028553
Displaying 1 - 3 of 3 reviews