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This book in the Edinburgh Textbooks in Empirical Linguistics series is a comprehensive introduction to the statistics currently used in corpus linguistics. Statistical techniques and corpus applications--whether oriented towards linguistics or language engineering--often go hand in glove, and corpus linguists have used an increasingly wide variety of statistics, drawing on techniques developed in a great many fields.This is the first one-volume introduction to the subject.
- Sales Rank: #2760725 in Books
- Published on: 1998-04-02
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x 1.00" w x 6.14" l, 1.14 pounds
- Binding: Paperback
- 272 pages
Review
Gives many instructive examples of statistical techniques applied to language data, provides exercises at the end of each chapter, and has a clear glossary. Year's Work in English Studies This book is essential for learning statistical analysis of texts. Most importantly, Oakes's is the only current corpus-linguistic book that devotes such a large portion of its pages to stylistics ! the whole book is worthwhile for the literary scholar. Language and Literature Gives many instructive examples of statistical techniques applied to language data, provides exercises at the end of each chapter, and has a clear glossary. This book is essential for learning statistical analysis of texts. Most importantly, Oakes's is the only current corpus-linguistic book that devotes such a large portion of its pages to stylistics ! the whole book is worthwhile for the literary scholar.
About the Author
Michael Oakes is Senior Lecturer in the School of Computing and Technology, University of Sunderland.
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Good Stats Reference Book for Linguists
By John M. Ford
Although a bit dated, this combination textbook/reference book remains useful and in print. It presents the basic statistical tools used to study large bodies of text and prepares readers for further study in a more software-oriented text such as Analyzing Linguistic Data: A Practical Introduction to Statistics using R or Quantitative Corpus Linguistics with R: A Practical Introduction.
The domain of linguistics-relevant statistics is covered in five well-organized chapters. Chapter 1: Basic Statistics covers introductory measures of variance and central tendency, then more intermediate topics such as comparing group scores and various measures of correlation. It concludes with summary treatments of loglinear modeling and Bayesian statistics. The second chapter covers Information Theory, from Shannon's initial formulation through stochastic processes and Markov models. The last section of chapter two applies these concepts to natural-language processing with examples from part-of-speech tagging, stylistics and information security.
Chapter 3: Clustering presents methods for finding structure in data, including factor analysis, principle components analysis, cluster analysis, and techniques specific to summarizing semantic similarity between words. Chapter 4: Concordancing, Collocations, and Dictionaries presents techniques for examining which words occur together, either in pairs or larger groupings. The techniques range from summary statistics to software tools that help linguists interactively explore word patterns. The final chapter, Literary Detective Work, is the most intriguing. It illustrates the value of these statistical techniques in analysis of writing style, resolving authorship disputes, and translating ancient languages. The examples are fascinating, but would be more so if additional detail were provided for each one.
I recommend this book for students learning about text analytics and as a reference for those who do research in this area. The frequent "As Used in Corpus Linguistics" sections are particularly helpful in explaining applied concepts. The book's statistical concepts remain sound, but the software references are a bit dated. I would like to see a new edition of the book that references the current set of software tools.
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