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Analyzing Linguistic Data: A Practical Introduction to Statistics using R Paperback – 6 Mar 2008

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Product details

  • Paperback: 368 pages
  • Publisher: Cambridge University Press; 1 edition (6 Mar. 2008)
  • Language: English
  • ISBN-10: 0521709180
  • ISBN-13: 978-0521709187
  • Product Dimensions: 17.4 x 2.1 x 24.7 cm
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Bestsellers Rank: 37,979 in Books (See Top 100 in Books)
  • See Complete Table of Contents

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Product Description

Book Description

A straightforward introduction to the statistical analysis of language, designed for those with a non-mathematical background. Using the leading statistics programme 'R', the reader is guided step-by-step through a range of data sets, aided by over 40 exercises with model answers. Suitable for all those working with quantitative language data.

About the Author

R. H. Baayen is Professor of Quantitative Linguistics at Radboud University of Nijmegen and the Max Planck Institute for Psycholinguistics, Nijmegen.

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3 of 4 people found the following review helpful By John M. Ford TOP 500 REVIEWER on 3 Jun. 2011
Format: Paperback
Having decided to tune up my R skills beyond the dabbling stage, I bought this book and signed up for an online class in R data handling. The course is very good, but this book is just as good or better--and it's cheaper by a factor of 10. I recommend the book. It is written to introduce linguistics students to basic statistical analysis in their discipline using R as their first tool. It works just as well for an SPSS-using psychologist who wants to learn R a little better and snoop in on what the linguists are doing.

R. Baayen's R book is well organized. The first two chapters encourage readers to sit down at their computer and type commands into the R command line. This hands-on introduction is supplemented by guidance on managing R sessions and creating command files. Subsequent chapters teach basic graphing techniques and statistical probability. The book then steps through the standard curriculum of introductory statistics, from simple t-tests through advanced regression modeling. Chapter 6 on clustering and classification gives this topic more attention that it receives in most introductory stats texts. The data sets and analysis tasks are drawn from applied linguistics and seem realistic and interesting--to this psychologist, anyway.

The book's instructional chapters are supported by helpful resources. The data sets and associated files are easily downloaded from the author's web site. The chapters are filled with example R code and output, allowing readers to follow examples closely and check their work. Back-of-the-book materials include answers to chapter exercises, a topical organization of R functions, and a very complete and up-to-date reference section.
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Format: Paperback Verified Purchase
Finally, an in depth treatment of statistics by a (type of) linguist. I think the take off and climb are far too steep for this book to serve as an introduction either to statistics or to R. But for a linguist who is familiar with both, this book will likely be very useful. Many of the example data sets are pretty complex, which may be a bit much for readers who find it hard enough just figuring out how to use R to do statistics.
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1 of 2 people found the following review helpful By Tareq on 26 July 2010
Format: Paperback
This is a recommended book for linguistics students. It helps you understand basic statistics as well mastering R for linguistic data analysis. It gives a very neat explanation for graphs as well.
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1 of 4 people found the following review helpful By STF on 30 Nov. 2009
Format: Paperback
I have only read one chapter of the book (a crashcourse for the R language), so I cannot say much about the content. It generally looks quite good, since it covers most issues in statistics which are relevant for linguistics.

I was a bit upset because I got a copy of the book with a defective cover where the word "Data" is missing. This is just a detail, but I think this is quite an unpleasant policy to sell defective copies over the internet. Such copies are usually destroyed or sold with a considerable discount. I tried to contact Amazon because of this, but the only option the webpage gives me is to return the item or ask for a replacement (I wonder if I get the same defective edition again). I neither want to return the book nor to get it replaced, since this would imply the additional trouble of sending it back. I just want Amazon/Cambridge Press to tell me the defects before I order the copy. Btw: My office-mate got a copy with the same cover from another seller, so this seems to be a new policy employed by Cambridge Press: get rid of bad copies over the internet. Not very nice.
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: 4 reviews
13 of 13 people found the following review helpful
Better Than an Online R Course 21 Mar. 2009
By John M. Ford - Published on Amazon.com
Format: Paperback Verified Purchase
Having decided to tune up my R skills beyond the dabbling stage, I bought this book and signed up for an online class in R data handling. The course is very good, but this book is just as good or better--and it's cheaper by a factor of 10. I recommend the book. It is written to introduce linguistics students to basic statistical analysis in their discipline using R as their first tool. It works just as well for an SPSS-using psychologist who wants to learn R a little better and snoop in on what the linguists are doing.

R. Baayen's R book is well organized. The first two chapters encourage readers to sit down at their computer and type commands into the R command line. This hands-on introduction is supplemented by guidance on managing R sessions and creating command files. Subsequent chapters teach basic graphing techniques and statistical probability. The book then steps through the standard curriculum of introductory statistics, from simple t-tests through advanced regression modeling. Chapter 6 on clustering and classification gives this topic more attention that it receives in most introductory stats texts. The data sets and analysis tasks are drawn from applied linguistics and seem realistic and interesting--to this psychologist, anyway.

The book's instructional chapters are supported by helpful resources. The data sets and associated files are easily downloaded from the author's web site. The chapters are filled with example R code and output, allowing readers to follow examples closely and check their work. Back-of-the-book materials include answers to chapter exercises, a topical organization of R functions, and a very complete and up-to-date reference section. Three separate indices help readers find references to datasets and R commands as well as general topics.

My knowledge of and skill with R has increased as a result of using this book. I feel well prepared to conduct analyses in R that I have done previously in SPSS because I have become familiar with not only specific commands, but with the R way of doing things. I'll be moving on to Quantitative Corpus Linguistics with R: A Practical Introduction to supplement my experience in text mining with a better understanding of what computational linguists do in R.
11 of 11 people found the following review helpful
Great if you know some statistics, a little R, and some linguistics 14 Nov. 2009
By Robert Felty - Published on Amazon.com
Format: Paperback Verified Purchase
This book is very well organized, and has a wealth of information. That being said, it is not for absolute beginners. It assumes that you already know a little bit about statistics, R, and linguistics. You should have some basic knowledge of t-tests, ANOVA and the like before reading. You should also go through some of the R tutorials if you have not used R before. Once you have that basic knowledge, this book will really help you learn how to do some advanced statistical analyses of your linguistic data. There are many code samples, including some R packages which you can download.
2 of 2 people found the following review helpful
I feel like a statistics pro because of this book 13 May 2015
By Joey Stanley - Published on Amazon.com
Format: Paperback Verified Purchase
I just wanted to add another, more recent review for this book. We used this book as the primary text in my "Quantitative Methods in Linguistics" course. I had never taken any sort of statistics before, so even things like a chi-squared test were foreign to me. But by the end, I was running a generalized linear mixed-model which includes a dozen variables, some random variables, and a dozen or so interactions between them all. I was able to interpret the output, and modify the model appropriately until I found the best one. I discovered some really interesting results from my data that I could not have found without this book. I went from a complete beginner to a total pro.

With that said, I should mention a few things. One, having some computing background will help a lot when reading this book. I imagine that without prior exposure to statistics or any sort of coding, the book would be a bit overwhelming. Knowing some statistics or coding beforehand will help. It should go without saying that the reader knows some linguistics as well.

Two, the book is starting to show its age. R has changed a bit in the past 5 years since it came out. The example code (that so graciously comes with the R package specifically written for the book, languageR) has a few inconsistencies and is even obsolete in some places--especially in the last chapter. For example, the Design package has been replaced by rms.

Third, I found it helpful to have a dataset ready to be analyzed. I gained a lot more from this book because I was able to apply it to my own dataset in addition to the examples.

I can't say for certain how this book compares to similar books. The two main ones I know about are Gries' Statistics for Linguistics with R and Johnson's Quantitative Methods In Linguistics. I haven't read either in much depth, but it appears that Gries' is more mathy, while Johnson's is more explicit on how to apply things to specific subfields. And while you'll get a ton more background in a standard introduction to statistics book, actual application to your own linguistic data--and how to do it in R--might be the best part of this book.

[Edit: One thing that that Baayen's book that I really miss in other books (Gries' and Johnson's) is that all the code for the entire book is in one file. Instead of having to sift through dozens of short snippets, the entire book is in one file. It makes things a lot easier to run. Also, what I took for granted while reading through this book is that it comes with its own R package "languageR" that has all the datasets built into it, not to mention a couple handy functions. Instead of going to the companion website and downloading files and having to worry about that, it's fully integrated into R itself. Extremely helpful!]

I thought the book was great. Again, I went from nothing to a pro in just four months. The statistics jargon I've heard and read in papers now makes a lot more sense and I can critically analyze others' methodologies. While Variationist Sociolinguistics and Laboratory Phonologists would probably get the most out of something like this, I think any linguist student should get some statistics background like the kind in this book.
1 of 1 people found the following review helpful
This books is a great tool for those who are in the area of linguistics in need of learning a statistical program 11 Nov. 2012
By Aimee - Published on Amazon.com
Format: Kindle Edition Verified Purchase
I bought the kindle version of this product which I found to be a better option for me than the paperback version. I am really satisfied with the product. The only negative aspect of having the kindle version of this book is that, unlike the paper back version, I cannot share it with anyone who doesn't have the kindle app. The content of the product itself is great and has proven to be a great book for learning R as a very useful tool for quantitative analysis in linguistics.
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