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Analyzing Linguistic Data
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Produktbeschreibungen
Über das Produkt
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.
Kurzbeschreibung
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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8 von 8 Kunden fanden die folgende Rezension hilfreich
Better Than an Online R Course
21. März 2009
Format:Taschenbuch|Von Amazon bestätigter 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.
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.
7 von 7 Kunden fanden die folgende Rezension hilfreich
Great if you know some statistics, a little R, and some linguistics
14. November 2009
Format:Taschenbuch|Von Amazon bestätigter 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.
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