Introductory Statistics with R (Statistics and Computing) |  | Author: Peter Dalgaard
Publisher: Springer
List Price: $59.95
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Rating:  24 reviews
Sales Rank: 20872
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
ASIN: 0387790535
Publication Date: August 15, 2008
Availability: Usually ships in 1-2 business days
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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:
Showing reviews 1-5 of 24
 Good for an introduction November 12, 2009
P. McCarren
This is a good book but it really is an introduction to statistics and a good introduction to basic R syntax. I use R quite a bit but I still forget some of the basics. This is a good book to quickly look up what you're trying to do and get the key R function name. R can be pretty painful. Ripley's "Modern Statistics with S" (R is basically S) would be good if you are going to stick with it, and it is a very good statistics reference book.Modern Applied Statistics with S
 Practical and concise October 7, 2009
Suhaida A. Selamat
If you need to learn to do some statistics fast, this is the book for you. Unlike the R book, which is more of a giant reference source, ISwR is more of a quick and dirty kind of thing. Easy to do. Liked it.
 A ok book October 4, 2009
Li Lishu (MT, USA)
It is a good book for a beginner though not as good as I expected.
Not enough examples for the coding part.
A Great Book on R June 15, 2009
Steven Lewis
Great well-written book. Good for learning how to run common statistical analyses in R. Chapter's 1,2, and 10 are also great for learning basic R data management. I would definitely recommend it to both new and existing users of R.
Too Superficial May 12, 2009
kmir (Nashville, TN US)
5 out of 5 found this review helpful
While most reviews on the book are positive, I would like to warn the potential buyer that this book *cannot* provide more than a very first quick look for someone who is totally new to R and wants to play around a little.
Here is the good stuff:
All the example code I tried (I am almost done with the entire book) works. Browsing this book and trying out the code exemplified is a no-brainer and completely frustration free.
Here is the not so good stuff:
If you seriously want to a) learn something about R or b) use a book to help you through serious analyses of your data, you should look somewhere else.
Regarding a), the R-intro file that comes with the R base installation contains more information on R as a programming language, how data are read by R (categorical variables as factors, e.g.) and how models can be specified. I hope that other books out there will provide even more information, but this R-intro is not a bad place to start. If you want to do b), this book will help you load your data into R (and even that is a little limited, see other reviews) and maybe create the most standard first analysis (but who is ever interested in that?) Not to mention the missing (and sometimes incorrect! - see page 119 on standard error of the mean confidence intervals) information on statistical procedures, you will need to look somewhere else to calculate basic statistics such as, e.g., partial or semi-partial correlations.
All in all I decided to give the book 3 stars based on its superficial user friendliness. You will not be able to really learn from this book, however.
Showing reviews 1-5 of 24
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