Introductory Statistics with R (Statistics and Computing) | 
 enlarge | Author: Peter Dalgaard
Publisher: Springer
Category: Book
List Price: $59.95
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Rating:  18 reviews
Sales Rank: 32008
Media: Paperback
Edition: 2nd
Pages: 364
Number Of Items: 1
Shipping Weight (lbs): 1.2
Dimensions (in): 9.1 x 6.1 x 0.8
ISBN: 0387790535
Dewey Decimal Number: 519
EAN: 9780387790534
Publication Date: August 15, 2008
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Product Description
R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development. This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. A supplementary R package can be downloaded and contains the data sets. The statistical methodology includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one- and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last six chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, survival analysis, Poisson regression, and nonlinear regression. In the second edition, the text and code have been updated to R version 2.6.2. The last two methodological chapters are new, as is a chapter on advanced data handling. The introductory chapter has been extended and reorganized as two chapters. Exercises have been revised and answers are now provided in an Appendix.
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| Customer Reviews: Read 13 more reviews...
 Twofold win: great introduction to useful statistics and R programming August 29, 2005
Isaac S. Kohane (Newton, MA USA)
22 out of 22 found this review helpful
Despite the web, there are learning curves sufficiently steep that a well-organized book is the most effective introduction. However, too many of these introductions, particularly in programming and/or statistics are written with low content and high redundancy or with impenetrably high-density content. So, it is a rare sign of pedagogical mastery combined with the genuine confidence of the experienced practioner when an introductory book manages to achieve a balance that is just right.
As I become more familiar with R, I still carry around this book in my briefcase for the occasional reread during which I uncover a nugget I had missed. When I have told this to my colleagues in computer science or bioinformatics, they immediately reveal that they share my enthusiasm for Dalgaard's work.
Let's be clear: this is a book that walks you through introductory and highly useful statistics while introducing you to the most effective ways to use R to perform these biostatistical analyses. It is not a programming book, nor is that its intent.
Very readable introduction April 24, 2003
Alan Mead (Lockport, IL United States)
39 out of 43 found this review helpful
This book provides a very readable introduction to basic statistical analysis using R (with occational references to S-Plus). The table of contents displays the topics and I thought they were generally well covered in enough detail to compute the statistics (but this is not a statistics text). Especially helpful are the additional analysis steps, such as graphing results, and the peripheral R issues. Small things I would change: expanded coverage of manipulating data (e.g., SPSS's RECODE, TEMPORARY, MERGE FILE,...), more explicit instructions on installing the example data (it's at the end of the installation Appendix), discussion of interactions in ANOVA and regression, discussion of ANCOVA, and finally I would have liked a quick overview of the available packages and the stats they provide. But these are small issues; it's a great book.
Good starter for R March 5, 2005
lelliott (San Antonio, TX USA)
13 out of 13 found this review helpful
I found this book very readable and a great reference for getting started with R. I was quickly able to run various tests from chi-square to logistic regression using this guide. I would agree that this would not be good for someone familiar with R, which is why it's called "Introductory". It also serves as a handy reference, providing easy look-up for how to accomplish various common (and some not so common) statistical tests.
Great book for bioinformatics November 22, 2005
Atul Butte (Stanford, CA USA)
7 out of 8 found this review helpful
This is a great book for bioinformaticians (from the introductory student to advanced practitioner) to introduce oneself to R and SPLUS. The book is tutorial-oriented, making it easy to follow.
Excellent resource September 22, 2007
David B. Thompson (Carson City, Nevada USA)
3 out of 3 found this review helpful
I bought this book a little over a year ago when a friend and colleague insisted I learn the R system for our collaborative work. I am not a professional statistician, but an engineer and researcher who needs and uses statistics in the course of my professional work.
I found this book approachable and informative from the non-professional perspective. (That is, from the viewpoint of a non-statistician.) I found enough examples to guide me through the process of bringing my datasets into the R environment, and then enough guidance to get me through the initial analyses necessary to make meaningful use of the statistical computations contained within the R system.
There are many other texts that treat the kinds of advanced statistics capability in the R system. Those are also necessary references for the non-statistician. There are also other texts on using the graphics subsystem present in R (which is substantial). Those references are also useful for preparation of reports and other written material.
But, this text is most useful as a primer for the system and is a first source on my shelf when I need to know the "how-to" of the basics. Then, if my needs are more substantial than those addressed by Dalgaard, I'll turn to other references.
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