Quantitative corpus linguistics with R : a practical introduction
Author(s)
Bibliographic Information
Quantitative corpus linguistics with R : a practical introduction
Routledge, 2017
2nd ed
- : hbk
- : pbk
Available at 22 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
-
Kobe Shoin Women's University Library / Kobe Shoin Women's College Library
: hbk801.04/23212341833
Note
Includes bibliographical references and index
Description and Table of Contents
Description
As in its first edition, the new edition of Quantitative Corpus Linguistics with R demonstrates how to process corpus-linguistic data with the open-source programming language and environment R. Geared in general towards linguists working with observational data, and particularly corpus linguists, it introduces R programming with emphasis on:
data processing and manipulation in general;
text processing with and without regular expressions of large bodies of textual and/or literary data, and;
basic aspects of statistical analysis and visualization.
This book is extremely hands-on and leads the reader through dozens of small applications as well as larger case studies. Along with an array of exercise boxes and separate answer keys, the text features a didactic sequential approach in case studies by way of subsections that zoom in to every programming problem. The companion website to the book contains all relevant R code (amounting to approximately 7,000 lines of heavily commented code), most of the data sets as well as pointers to others, and a dedicated Google newsgroup. This new edition is ideal for both researchers in corpus linguistics and instructors who want to promote hands-on approaches to data in corpus linguistics courses.
Table of Contents
Chapter 1. Introduction
Chapter 2. The Four Central Corpus-Linguistic Methods
Chapter 3. An Introduction to R
Chapter 4. Some Basic Statistical Notions and Tests
Chapter 5. Using R in Corpus Linguistics: Case Studies
Chapter 6. Next steps
by "Nielsen BookData"