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A First Course in Statistical Programming with R Paperback – 13 Dec 2007


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Product details

  • Paperback: 172 pages
  • Publisher: Cambridge University Press; 1 edition (13 Dec. 2007)
  • Language: English
  • ISBN-10: 0521694248
  • ISBN-13: 978-0521694247
  • Product Dimensions: 18.9 x 1 x 24.6 cm
  • Average Customer Review: 3.5 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Bestsellers Rank: 624,722 in Books (See Top 100 in Books)
  • See Complete Table of Contents

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Review

'… with this book, you can be up and running, doing very advanced work with R in a matter of minutes. Using a series of code examples, the authors take you through many of the basic capabilities of the package. All that is needed to follow the examples is a basic understanding of control constructs such as the if-then, loops and functions as well as knowledge of the underlying mathematics.' Charles Ashbacher, Journal of Recreational Mathematics

Book Description

The only introduction you'll need to start programming in R. Co-written by one of the R Core Development Team, and by an established R author, the book includes real R code that complies with the standards of the language. Exercises and end-of-chapter reviews help you progress confidently through the book.

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16 of 16 people found the following review helpful By Andrew Dalby VINE VOICE on 17 Dec. 2008
Format: Paperback Verified Purchase
I have been using R in statistics courses for a few years and there are many introductions to R that cover the command structure and the statistical techniques, but none of them look at R as a programming language and take you through the steps of learning to program with R.

This book takes you from the first simple steps through to simulation, matrices and iterative optimisation. It also includes a guide for good programming practice. It includes an explanation of Monte Carlo integration that anyone can understand and shows the benefits of learning through practice. This book makes probability so much more accessible to students by letting them see what is actually happening in a graphical and practical way.

I think the book is fantastic and well worth the money.
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Format: Paperback Verified Purchase
Very nice book, although it does require some advanced prior experience with programming and knowledge of math concepts, etc. So I don't think this is a book for people starting to learn R. However, after having some experience with R you can improve your skills with this book.
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3 of 6 people found the following review helpful By C. J. Joyce on 19 Aug. 2010
Format: Paperback
Having done a reasonable job of introducing the basic syntax of the R programming language, the book then lurches into some rather advanced and specialist subjects, for example dedicating a whole section to algorithms for generating random numbers (for an introductory text, you would probably just want to know about the rnorm function).
If you are interested in Monte Carlo simulation or numerical optimisation using the R language, this is the book for you. Readers hoping to learn to use R to perform standard statistical testing will be disappointed.
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0 of 4 people found the following review helpful By T on 30 Dec. 2010
Format: Paperback
didn't excatly find what I was looking for in the book.

Could be laid out a bit better.
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: 12 reviews
4 of 4 people found the following review helpful
Beginner text with less of a statistical emphasis 7 Nov. 2010
By StanleyBruce - Published on Amazon.com
Format: Paperback
Despite its title, this book approaches teaching R from less of a statistical perspective than most other introductory texts on R. There are other texts that I would suggest (such as Verzani or Dalgaard) for those looking to learn how to do statistical analyses with R.
As some of the other reviewers have noted, this book is not comprehensive (I'd have rated it 3 and a half stars if that were possible). Also this book doesn't seem to have an accompanying website which might have added extra value.
For most potential R users, I'd recommend this book only if it were available at a lower price than most of its rivals. On the other hand, there are some important topics that are covered here in a more accessible manner than you are likely to find elsewhere. There is some useful explanation of low level graphics functions in Chapter 3. In particular, the introductions to Simulation (Chapter 5); Computational linear algebra (Chapter 6); and Numerical optimization (Chapter 7) are worth checking out. In my estimation, this book would be most useful for someone interested in introducing R to capable secondary students who might want to use R as a computational tool for a range of purposes including, but not limited to, data analysis. I think this would be a very useful enterprise, and for such a purpose I would recommend this particular book.
13 of 18 people found the following review helpful
Good book; Not quite whtt I was looking for, though 30 Jun. 2009
By A. KEITH - Published on Amazon.com
Format: Paperback Verified Purchase
This is a really well written book and does everything it said it would do. The only problem was that I was looking for a book that was more geared towards learning R, than a book on learning statistics. The book is surprisingly cursory in regards to leading the reader through the structurees and approach that R takes to solving problems. I found that most of the discussions of R's syntax to be incredibly lacking and its discussion of the how the various features of R to be very disappointingly poor for someone who is trying to learn R as a novice. I have spent most of my 30 years in the workforce learning a variety of languages and am used to "sefl study" challenges...but I have yet to find anything ever remotely similar to what almost every other language provides...an introductory tutorial that focuses on the language rather than all the cool things you can do with the language. This book is the losest so far; but is still, in my opinion, not a very useful or productive approach to learning R.
4 of 5 people found the following review helpful
Easy to understand introduction to "R" that has sufficient breadth to be used in a course 7 Sept. 2009
By Charles Ashbacher - Published on Amazon.com
Format: Paperback
Given that it is open source and easy to use, the programming package "R" is a natural choice for courses in statistics where a fundamental component is programming. Provided of course that an understandable text is available.
This book satisfies that requirement, making the fundamentals of programming as implemented in "R" accessible to the programming novice. Given that the mathematical coverage is a bit advanced, the prerequisites are mathematical in nature with precalculus a necessity and calculus very helpful.
While the basics of statistical programming are covered in sufficient detail, some more advanced topics in the area of numerical analysis are also included. Those topics are:

*) Computational linear algebra
*) Numerical optimization
*) Linear programming

If you are looking for an inexpensive computational package that your students can download on their laptops for use in a course on statistical programming, then "R" is a natural choice. With this textbook, it also becomes a practical one.
14 of 20 people found the following review helpful
A solid week's worth of material. 25 Mar. 2008
By Larry Seligman - Published on Amazon.com
Format: Paperback
It's nice in that it gives you problems and solutions to the problems, so you can teach yourself the language. But it is not nearly comprehensive enough to be a reference book. If you can afford it, buy this much more comprehensive, but still good for beginners, book instead:The R Book

Now if you just want to explore R some and are looking for a lower cost book with which to do so, or want a structured book with problems and exercises, then this Braun and Murdoch book is fine.
Organizational issues 19 Mar. 2015
By Phil Ganz - Published on Amazon.com
Format: Paperback Verified Purchase
The organization of this book is somewhat nonsensical and after working through the entire thing, I'm not sure who the intended audience is. For example, some of the solutions to the exercises at the end of section 4.1.1, which introduces the reader to for() loops, also require the use of while() loops, which aren't introduced until section 4.1.3. The result: someone (okay you guys, it's me) spends time trying to solve the question with the tool they've been given (for() loops) only to discover that the solution requires a tool not yet provided to them (while() loops). If the book is directed at people who already have a working knowledge of these functions, then it shouldn't spend the page space explaining them. If the book is geared toward people who are completely new to these functions, then the solutions to the exercises should be attainable using only those functions that have been introduced to the reader by that point. The current organization makes this "first" course needlessly frustrating.
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