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Beginning R: The Statistical Programming Language Paperback – June 5, 2012

ISBN-13: 978-1118164303 ISBN-10: 111816430X Edition: 1st

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Beginning R: The Statistical Programming Language + The Art of R Programming: A Tour of Statistical Software Design + R for Everyone: Advanced Analytics and Graphics (Addison-Wesley Data & Analytics Series)
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Product Details

  • Paperback: 504 pages
  • Publisher: Wrox; 1 edition (June 5, 2012)
  • Language: English
  • ISBN-10: 111816430X
  • ISBN-13: 978-1118164303
  • Product Dimensions: 7.4 x 0.9 x 9.2 inches
  • Shipping Weight: 1.8 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Best Sellers Rank: #525,961 in Books (See Top 100 in Books)

Editorial Reviews

From the Back Cover

Gain better insight into your data using the power of R

While R is very flexible and powerful, it is unlike most of the computer programs you have used. In order to unlock its full potential, this book delves into the language, making it accessible so you can tackle even the most complex of data analysis tasks. Simple data examples are integrated throughout so you can explore the capabilities and versatility of R. Along the way, you'll also learn how to carry out a range of commonly used statistical methods, including Analysis of Variance and Linear Regression. By the end, you'll be able to effectively and efficiently analyze your data and present the results.

Beginning R:

  • Discusses how to implement some basic statistical methods such as the t-test, correlation, and tests of association

  • Explains how to turn your graphs from merely adequate to simply stunning

  • Provides you with the ability to define complex analytical situations

  • Demonstrates ways to make and rearrange your data for easier analysis

  • Covers how to carry out basic regression as well as complex model building and curvilinear regression

  • Shows how to produce customized functions and simple scripts that can automate your workflow

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About the Author

Dr. Mark Gardener is an ecologist, lecturer, and writer working in the UK. He is currently self-employed and runs courses in ecology, data analysis, and R for a variety of organizations.

More About the Author

My latest book "Community Ecology: Analytical Methods Using R and Excel" is now in print. The study of ecological community data involves many methods of analysis. In this book you will learn many of the mainstays of community analysis including: diversity, similarity and cluster analysis, ordination and multivariate analyses. This book is for undergraduate and postgraduate students and researchers seeking a step-by-step methodology for analysing plant and animal communities using R and Excel.

The next project is about using Excel to manage data most effectively. The title is "Managing data using Excel: organising, summarizing and visualizing scientific data". This should be in print later in the summer 2014.

I started out as an optician but returned to science and completed my education with a degree from the Open University. I always wanted to be an ecologist and my degree enabled me to undertake research and I later gained a PhD in pollination ecology.

I've worked around the world and carried out field work in Australia and the United States as well as throughout the UK. After returning from research at the University of Hawai'i I began to do more teaching. I work as an Associate Lecturer with the Open University and also with the Field Studies Council.

More recently I have begun to write about ecology and science and in particular the process of collecting and analysing data. I have become familiar with the R program for statistical computing (open sources and free) and run courses in learning R as well as writing about it (see my website

My first book: "Statistics for Ecologists" is about the process of data analysis and is more than just a recipe for carrying out various statistical analyses. I've included notes on the collecting of data, and the writing up of the results as well as details about a range of analytical methods.

My last book "Beginning R" is aimed at teaching users how to get to grips with this powerful and flexible program. This book will be useful for anyone who needs to analyse datu, not just ecologists.

"The Essential R Reference". A reference guide for R, the statistical programming language, this is a kind of cross between a dictionary, thesaurus and glossary. I hope that it will be useful to new users and old hands alike.

Customer Reviews

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Most Helpful Customer Reviews

6 of 8 people found the following review helpful By BoroTurtle on May 8, 2013
Format: Paperback Verified Purchase
I have experience with statistics, SAS, and C programming, but I had no experience with R. The book has been quite useful for learning the basics of R programming. The features I particularly like are: (1) end of chapter summaries, (2) practice problems, with solutions at the end of the book, and (3) clearly written explanations of 'How It Works'.

The author covers how to use R to conduct statistical analyses that would be covered in a basic or advanced undergraduate statistics class. As noted in another review, the focus is on how to conduct an analysis (e.g., t-test), not why a t-test would be appropriate.

The book would be a great companion to a statistics book such as Howell's Statistical Methods for Psychology. Students who are enrolled in a statistics class or have had a statistics class and want to learn R may benefit the most from the book. The practice problems with solutions make it quite useful for self-teaching.
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5 of 7 people found the following review helpful By uberstomping on August 21, 2013
Format: Kindle Edition Verified Purchase
I read the book from the perspective of an experienced software developer and found that the book described R's functions and capabilties in a manner that was too simple and from my perspective and didn't require the level of details provided in the book. But with that being said, the book would be perfect for perhaps researchers or scientists with a less-strong programming background because it guides the users through the basics of beginning data analyses with R with thorough examples and exercises. I found the book requires a grasp of statistics to really appreciate the content (even though some concepts are explained). Only one chapter seemed relevant for the actual "programming" of R. On the other hand I got a decent enough overview of the nature of functions built into R.
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7 of 11 people found the following review helpful By Not_A_Bot_12 on November 20, 2012
Format: Kindle Edition Verified Purchase
Updating my review and raised it a star...
This is a good third level book. It makes very little use of any 3rd party packages. Just native R functions.

After you have played with R for a semester, this may be a good follow on book. It will improve your R knowledge and decide how deep you want to go into programming with R.

There is 5 different ways to do stuff, so ever book shows a different way. Not relaying on packages gives some "behind the scenes" on what is happening.

********Original Review********
The book really shouldn't start with Beginning R. On the book cover it says programmer to programmer in small text in the upper right hand corner. Programmers is who the book is directed at.

I bought the book because it had Beginning in the title and the kindle version price was reasonable.

1. The book assumes you have the required math/statistics knowledge already.

2. The book assumes you have a good understanding of programming already.

Based on my quick look at the book last night this isn't a book for someone familiar with the research methods based approach. The use of the word "independent" is only 3 times in the context of "independent variable" in the entire book. There is 3 sample PDFs on the books web site. just google for it.

I will update my review in a couple months after I have progressed in my knowledge more, but wanted to help out those who were considering this book.

Also the "R for dummies" and "Art of R programming" are not intro books either. The R for dummies book is more disappointing as dummies books are usually good intro books.
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0 of 1 people found the following review helpful By Dimitri Shvorob on August 17, 2014
Format: Paperback
I have given Mark Gardener grief over his "Essential R" and, sorry, this book, too, does not scream "painstaking writing", "originality" or "teaching expertise". And yet the overall impression is quite positive: the author's R experience and straightforward writing, and simple but attractive typesetting, produce a nice collection of R vignettes, spanning R basics and simple statistics. Coverage is by no means comprehensive, and "base" R alone is discussed - a problem, as so many "add-on" packages have become standard - but the book does cover a lot of ground, and does not cost much. I would still recommend Robert Kabacoff's "R in Action" as the best introduction to R, but for the more timid beginners, "Beginning R", alongside Paul Teetor's "R Cookbook", could be a sensible starting point.
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