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9 of 10 people found the following review helpful:
5.0 out of 5 stars
Read this after Using R for Introductory Statistics, December 18, 2008
This review is from: Introductory Statistics with R (Statistics and Computing) (Paperback)
This is a great intro-intermediate R book for intro stats.
I recommend you to read "Using R for Introductory Statistics" by John Verzani first, if you know general things about stats.
Using R is written in more step-by-step way and there are a lot of repetitions that helped you learn R language by merely reading through the book.
After you finish Using R, proceed to Dalgaard's book.
As one of the reviewer said, Dalgaard's book can be a concise reference book since it covers more stuff than Using R does.
It is a nice, compact book on many techniques, but it sometimes lacks suffice explanations.
This is why Using R should come first and Dalgaard's book comes next.
If you finish these books, you are ready to explore other R and S-Plus books as you need.
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18 of 23 people found the following review helpful:
3.0 out of 5 stars
Too Superficial, May 11, 2009
This review is from: Introductory Statistics with R (Statistics and Computing) (Paperback)
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.
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1 of 1 people found the following review helpful:
5.0 out of 5 stars
Excellent intro text for programming stats in R, September 28, 2011
This review is from: Introductory Statistics with R (Statistics and Computing) (Paperback)
R is a useful freeware that can represent a hurdle to students and/or professionals who do not have formal training in computer programming. This book helps to clear those hurdles, and introduces a solid foundation from which statistics users can build new tools for their specific analyses. The rest of this review is broken up for experienced and new users. ****If you do not have a solid foundation in statistics, this book is not going to help you bridge that gap. Although the title is "Introductory Statistics with R" the author is clear that this is a book to learn how to program intro stats with R, and is not designed to teach any statistics tools. The author assumes you understand statistics and does not clarify statistics terms like p-value, test statistic, degrees of freedom, ANOVA, and the like. **** New to R:
Although it may sound like a conundrum, the only way to learn a program is to program. Thankfully learning R can be easy, since the program is free, installs well on nearly all machines, and has detailed help files in various languages around the world. This is an excellent book for the R beginner, but I must stress the importance of ACTUALLY PROGRAMMING while you read this book. You CAN NOT read this book cover to cover and expect to learn R, programming doesn't work that way. This book can be a great resource for people who are brand new to R, but it requires hands on utilization of the source codes provided. Thankfully, this step is made that much easier for new users with a detailed explanation of how to obtain the ISWR package used with this text. Like everything in R, packages are free, and contain suites of functions and sometimes data. All the code in this book utilizes data from the ISWR package, so it will be easy to implement the code yourself and get the same results as the author. Familiar with R:
Someone familiar with the notation in R can read this book cover to cover and find it enlightening. I had been programming in R for coursework in undergraduate statistics for four years before I found this text. It has a lot of useful data management code that people who taught themselves or learned for classes not dedicated to teaching the program will probably find useful. I found a lot of time-saving code that I wish I had known years ago!
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