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Corpus Linguistics And Statistics With R Introduction To Quantitative Methods In Linguistics 1st Edition Guillaume Desagulier Auth

  • SKU: BELL-6841284
Corpus Linguistics And Statistics With R Introduction To Quantitative Methods In Linguistics 1st Edition Guillaume Desagulier Auth
$ 31.00 $ 45.00 (-31%)

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Corpus Linguistics And Statistics With R Introduction To Quantitative Methods In Linguistics 1st Edition Guillaume Desagulier Auth instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 7.42 MB
Pages: 359
Author: Guillaume Desagulier (auth.)
ISBN: 9783319645704, 9783319645728, 3319645706, 3319645722
Language: English
Year: 2017
Edition: 1

Product desciption

Corpus Linguistics And Statistics With R Introduction To Quantitative Methods In Linguistics 1st Edition Guillaume Desagulier Auth by Guillaume Desagulier (auth.) 9783319645704, 9783319645728, 3319645706, 3319645722 instant download after payment.

This textbook examines empirical linguistics from a theoretical linguist’s perspective. It provides both a theoretical discussion of what quantitative corpus linguistics entails and detailed, hands-on, step-by-step instructions to implement the techniques in the field. The statistical methodology and R-based coding from this book teach readers the basic and then more advanced skills to work with large data sets in their linguistics research and studies. Massive data sets are now more than ever the basis for work that ranges from usage-based linguistics to the far reaches of applied linguistics. This book presents much of the methodology in a corpus-based approach. However, the corpus-based methods in this book are also essential components of recent developments in sociolinguistics, historical linguistics, computational linguistics, and psycholinguistics. Material from the book will also be appealing to researchers in digital humanities and the many non-linguistic fields that use textual data analysis and text-based sensorimetrics. Chapters cover topics including corpus processing, frequencing data, and clustering methods. Case studies illustrate each chapter with accompanying data sets, R code, and exercises for use by readers. This book may be used in advanced undergraduate courses, graduate courses, and self-study.

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