Beginning R: The Statistical Programming Language Paperback – Jun 5 2012
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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.
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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Visit the Beginning R website at www.wrox.com/go/beginningr
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.
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Most Helpful Customer Reviews on Amazon.com (beta)
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.
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.
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.