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Review
"I would recommend this book to those who need to teach statistics via the medium of R and those self learners who want to acquire the basic techniques of statistics together with powerful statistical software." (Technometrics, May 2006)
"…will provide you with enhanced statistical insights…and access to a free and powerful computing language." (Clinical Chemistry, May 2006)
"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)
"…offers a demanding, non–calculus–based coverage of such standard topics as hypothesis testing, modeling, regression, ANOVA, and count data." (CHOICE, November 2005)
Review
"I would recommend this book to those who need to teach statistics via the medium of R and those self learners who want to acquire the basic techniques of statistics together with powerful statistical software." (Technometrics, May 2006)
"…will provide you with enhanced statistical insights…and access to a free and powerful computing language." (Clinical Chemistry, May 2006)
"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)
"…offers a demanding, non–calculus–based coverage of such standard topics as hypothesis testing, modeling, regression, ANOVA, and count data." (CHOICE, November 2005)
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Most Helpful Customer Reviews
9 of 9 people found the following review helpful
Format:Paperback
This is a book that you learn R as well as statistics, with all examples available very applicable to real life scenarios. I am a first year PhD student in biology who needs to start picking up Maths as well as a program to analysis. This book so far enables me to learn R as well as recap some of the fundamentals in statistics.
22 of 23 people found the following review helpful
Format:Paperback|Amazon Verified Purchase
It's a long time since I did any statistics, and it wasn't in much depth. My workplace has a lot of time series data stored in a database; I plan on using R to provide automatic anomaly detection, to aid in capacity planning, and business development -- classic data warehouse tasks, in other words.
This book is very helpful in some respects. The pragmatic approach described (in particular the sections on model fitting) seems very good. I enjoyed the inclusion of some historical background on the derivation of the statistical methods, and the chatty style didn't grate. Some of the practical hints and tips, eg how not to build a data frame, seemed as if they would be good for complete newcomers to R. The book essentially fulfils its title as an introduction to statistics using R.
My particular interest in time series isn't addressed in this book -- I also bought "The Analysis of Time Series: An Introduction".
Now the negatives. I generally like "Statistics: An Introduction Using R", so don't take this as advice not to buy it -- I just hope these things are fixed in a later edition. My quibbles are largely stylistic or production related.
* Despite the author's assertion that the book assumes no mathematical knowledge from time to time it dives into notation that isn't adequately explained for the complete novice. It seems as if the depth of prior knowledge varies from chapter to chapter; at some points in the book I felt that it was pitched at a much less experienced audience, and at others that it was right over my head. It seems to fall between the two stools of being an introduction to stats in general, and an introduction to stats with R on the other. Assuming no /a priori/ knowledge seems to me to be the safer course, and was certainly what I was looking for.
* The Helvetica font for presenting the source code is irritating; in several cases the characters are ambiguous, and it's generally hard to read. Transcripts of output from the software are presented in a fixed-width font; surely it would be natural to do the same for the input? In fact, the typography generally is poor, and is put to shame by the beautiful Dalgaard book "Introductory Statistics with R".
* Although examples are apparently available online, some extra information in the book on graphical techniques (eg the code to generate some of the figures) would have been appreciated.
* A nitpick: the assumption is made that R is running on the Windows platform (presumably the author's university labs run on this OS). It would be nice to see a short appendix of platform-specfic information, eg about running R on Mac OS X, Solaris, or Linux. The information on data entry, for example, makes the assuption that Microsoft Excel will be the tool of choice -- I plan on pullig information directly out of a database, and would rather see a section on interfacing R to a proper data source, rather than a glorified grid control.
* A final nitpick -- in one place "lose" is misspelt as "loose". I physically wince on reading this page. I haven't spotted any other typos though.
This book is very helpful in some respects. The pragmatic approach described (in particular the sections on model fitting) seems very good. I enjoyed the inclusion of some historical background on the derivation of the statistical methods, and the chatty style didn't grate. Some of the practical hints and tips, eg how not to build a data frame, seemed as if they would be good for complete newcomers to R. The book essentially fulfils its title as an introduction to statistics using R.
My particular interest in time series isn't addressed in this book -- I also bought "The Analysis of Time Series: An Introduction".
Now the negatives. I generally like "Statistics: An Introduction Using R", so don't take this as advice not to buy it -- I just hope these things are fixed in a later edition. My quibbles are largely stylistic or production related.
* Despite the author's assertion that the book assumes no mathematical knowledge from time to time it dives into notation that isn't adequately explained for the complete novice. It seems as if the depth of prior knowledge varies from chapter to chapter; at some points in the book I felt that it was pitched at a much less experienced audience, and at others that it was right over my head. It seems to fall between the two stools of being an introduction to stats in general, and an introduction to stats with R on the other. Assuming no /a priori/ knowledge seems to me to be the safer course, and was certainly what I was looking for.
* The Helvetica font for presenting the source code is irritating; in several cases the characters are ambiguous, and it's generally hard to read. Transcripts of output from the software are presented in a fixed-width font; surely it would be natural to do the same for the input? In fact, the typography generally is poor, and is put to shame by the beautiful Dalgaard book "Introductory Statistics with R".
* Although examples are apparently available online, some extra information in the book on graphical techniques (eg the code to generate some of the figures) would have been appreciated.
* A nitpick: the assumption is made that R is running on the Windows platform (presumably the author's university labs run on this OS). It would be nice to see a short appendix of platform-specfic information, eg about running R on Mac OS X, Solaris, or Linux. The information on data entry, for example, makes the assuption that Microsoft Excel will be the tool of choice -- I plan on pullig information directly out of a database, and would rather see a section on interfacing R to a proper data source, rather than a glorified grid control.
* A final nitpick -- in one place "lose" is misspelt as "loose". I physically wince on reading this page. I haven't spotted any other typos though.
14 of 15 people found the following review helpful
Format:Paperback
This book achieves what I considered impossible - it genuinely explains how to use the magnificent and FREE statistics package R AND teach you statistics at the same time from scratch. Michael Crawley is a born teacher and writer. As I was working through the book, I kept thinking 'How is the man managing it? This is astonishing' Look at most Stats books and try and find a few with ANY reviewers.. This is the best Stats book I've ever read. BUY IT
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Most Recent Customer Reviews
good book to explain a complicated software
very well written to simplify an otherwise very difficult software. it explains all the basics and the advanced feature of R. useful for any level of knowledge.
Published 7 months ago by domenico
Great book for self learning of statistics and R
This is a great book to revise basic statistics and at the same time get used to work with R.
Simple and real examples are given in the book. Read more
Simple and real examples are given in the book. Read more
Published 12 months ago by Katarina
Statistics : An Introduction using R
I bought this book firstly to refresh my memory about stats but also to get an overview of R and start using it quickly. Read more
Published 18 months ago by SteveC
Useful resource, but shouldn't be an introduction to R or statistics
This book has a lot of useful material, but sets itself an impossible task: trying to introduce statistics at the same time as trying to introduce R. Read more
Published 19 months ago by J. Minton
A companion learning aid, but not a primer
I disagree with some of the reviewers regarding the suitability of this book as a primer for the R language - the freely available tutorials on the R project website are far... Read more
Published on 22 Dec 2009 by C. J. Joyce
Caught in the middle
This book is caught between explaining statistics and explaining "R" and falls down somewhere between the two without explaining either in the detail or style required.
Published on 13 April 2009 by jdj
Excellent book, but ...
Crawley's book is a very useful introduction to statistical thinking and the use of R as a statistical calculator and a graph generator. The book really deserves five stars. Read more
Published on 16 Feb 2009 by S. Butler
Not for beginners
Despite claiming to be a resource for those unfamiliar with statistics or maths, within 2 paragraphs this books fails to keep to this concept. Read more
Published on 22 Nov 2008 by L. Clifforde
An excellent statistics book as well as an R book
I've been hoping to find a book that would allow me to recommend R for my undergraduate and postgraduate students. This is undoubtedly it. Read more
Published on 31 July 2006 by Dr. Colin Turner
Practical Introduction to Statistics
A great book that explains as it goes along; there are occasional unexplained terms that were slightly off-putting at first, but trust the guy, you'll know exactly what he's... Read more
Published on 27 July 2005
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