Learning RStudio for R Statistical Computing

by Mark Van Der Loo, Edwin De Jonge

If you need to create and manage complex statistical analysis projects, this book could be a catalyst for great things. In clear, practical chapters it teaches you how to employ Rstudio's powerful features to perform R statistical computing. Overview In Detail Data is coming at us faster, dirtier, and at an ever increasing rate. The necessity to handle many, complex statistical analysis projects is hitting statisticians and analysts across the globe. This book will show you how to deal with it like never before, thus providing an edge and improving productivity. "Learning RStudio for R Statistical Computing" will teach you how to quickly and efficiently create and manage statistical analysis projects, import data, develop R scripts, and generate reports and graphics. R developers will learn about package development, coding principles, and version control with RStudio. This book will help you to learn and understand RStudio features to effectively perform statistical analysis and reporting, code editing, and R development. The book starts with a quick introduction where you will learn to load data, perform simple analysis, plot a graph, and generate automatic reports. You will then be able to explore the available features for effective coding, graphical analysis, R project management, report generation, and even project management. "Learning RStudio for R Statistical Computing" is stuffed with feature-rich and easy-to-understand examples, through step-by-step instructions helping you to quickly master the most popular IDE for R development What you will learn from this book Approach A practical tutorial covering how to leverage RStudio functionality to effectively perform R Development, analysis, and reporting with RStudio. Who this book is written for The book is aimed at R developers and analysts who wish to do R statistical development while taking advantage of RStudio functionality to ease their development efforts. Familiarity with R is assumed. Those who want to get started with R development using RStudio will also find the book useful. Even if you already use R but want to create reproducible statistical analysis projects or extend R with self-written packages, this book shows how to quickly achieve this using RStudio.

Genres: Technology, Nonfiction

126 pages, Paperback

First published December 24, 2012

Reviews

[Renato Vitolo · Rating 5 out of 5]

I have just had the pleasure of reading "Learning RStudio for R Statistical Computing" and found it very useful for my work as a quantitative analyst.

The book offers a self-contained introduction to RStudio, an extremely well-designed and functional interface to the R interpreter. Given its strong "hands-on", "get-things-done" approach, the book provides a rather complete introduction for the beginner, be she an experienced data analyst who is not familiar with R, or an altogether inexperienced data analyst.

While the book does not present advanced statistical theories or methods, it focuses on how to get started with data analysis, from setting up and managing a project (Chapter 4), through data exploration (Chapter 3 on data viewing and plotting), down to generating reports (Chapter 5).

As an expert R developer, I found the last chapters particularly useful for me: they provide simple access to advanced features of RStudio, such as the automatic generation of reports in different formats (HTML, LaTeX, Chapter 5) and the development of an R package for distribution among colleagues or in the web (Chapter 6).

What I find particularly valuable in the book is its conciseness, whereby many topics are introduced with minimal examples, retaining, however all the essential ingredients and bibliographic references. This allows a hasty (or lazy) reader to quickly skim through and reach her goal.

I therefore definitely recommend this book as a handy swiss-knife for the eager (wannabe) data analyst.

[Venkatesh-Prasad · Rating 2 out of 5]

The book does a good job of being a brief introduction to RStudio. The book does not provide any useful information about RMarkdown, RHTML, and such. This latter aspect is disappointing.