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100   $a20171118d2017      u|         0
101 0 $aeng
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182   $cc$2rdamedia
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200 10$aCorpus Linguistics and Statistics with R $eIntroduction to Quantitative Methods in Linguistics /$fby Guillaume Desagulier
205   $a1st ed. 2017.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017.
215   $a1 online resource (XIII, 353 p. 98 illus., 55 illus. in color.)
225 1 $aQuantitative Methods in the Humanities and Social Sciences,$x2199-0956
311   $a3-319-64570-6 
327   $aIntroduction -- R Fundamentals -- Digital Corpora -- Processing and Manipulating Character Strings -- Applied Character String Processing -- Summary Graphics for Frequency Data -- Descriptive Statistics -- Notions of Statistical Testing -- Association and Productivity -- Clustering Methods.
330   $aThis textbook examines empirical linguistics from a theoretical linguist?s perspective. It provides both a theoretical discussion of what quantitative corpus linguistics entails and detailed, hands-on, step-by-step instructions to implement the techniques in the field. The statistical methodology and R-based coding from this book teach readers the basic and then more advanced skills to work with large data sets in their linguistics research and studies. Massive data sets are now more than ever the basis for work that ranges from usage-based linguistics to the far reaches of applied linguistics. This book presents much of the methodology in a corpus-based approach. However, the corpus-based methods in this book are also essential components of recent developments in sociolinguistics, historical linguistics, computational linguistics, and psycholinguistics. Material from the book will also be appealing to researchers in digital humanities and the many non-linguistic fields that use textual data analysis and text-based sensorimetrics. Chapters cover topics including corpus processing, frequencing data, and clustering methods. Case studies illustrate each chapter with accompanying data sets, R code, and exercises for use by readers. This book may be used in advanced undergraduate courses, graduate courses, and self-study.
410  0$aQuantitative Methods in the Humanities and Social Sciences,$x2199-0956
606   $aStatistics 
606   $aGrammar
606   $aComputational linguistics
606   $aR (Computer program language)
606   $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008
606   $aGrammar$3https://scigraph.springernature.com/ontologies/product-market-codes/N24000
606   $aComputational Linguistics$3https://scigraph.springernature.com/ontologies/product-market-codes/N22000
606   $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040
615  0$aStatistics .
615  0$aGrammar.
615  0$aComputational linguistics.
615  0$aR (Computer program language).
615 14$aStatistics and Computing/Statistics Programs.
615 24$aGrammar.
615 24$aComputational Linguistics.
615 24$aStatistics for Social Sciences, Humanities, Law.
676   $a410.188
700   $aDesagulier$b Guillaume$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767498
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910254307203321
996   $aCorpus Linguistics and Statistics with R$91562544
997   $aUNINA