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Analyzing Linguistic Data: A Practical Introduction to Statistics using R [Kindle Edition]

R. H. Baayen

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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.


Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.


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Die hilfreichsten Kundenrezensionen auf (beta) 4.8 von 5 Sternen  4 Rezensionen
12 von 12 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Better Than an Online R Course 21. März 2009
Von John M. Ford - Veröffentlicht auf
Format:Taschenbuch|Verifizierter Kauf
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.
10 von 10 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Great if you know some statistics, a little R, and some linguistics 14. November 2009
Von Robert Felty - Veröffentlicht auf
Format:Taschenbuch|Verifizierter Kauf
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.
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen I feel like a statistics pro because of this book 13. Mai 2015
Von Joey Stanley - Veröffentlicht auf
Format:Taschenbuch|Verifizierter Kauf
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 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen This books is a great tool for those who are in the area of linguistics in need of learning a statistical program 11. November 2012
Von Aimee - Veröffentlicht auf
Format:Kindle Edition|Verifizierter Kauf
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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