Statistical Methods for Linguistics
This section lists books on statistical methods in Linguistics. Books specifically on statistical analysis in Linguistics using the R programming environment are listed in the section below.
Statistics for Linguists: A Step-by-Step Guide for Novices by Publication Date: 2015Linguists with no background in statistics will find this book to be an accessible introduction to statistics. Concepts are explained in non-technical terms, and mathematical formulas are kept to a minimum. The book incorporates SPSS, which is a statistics package that incorporates a point and click interface rather than complex line-commands.
Statistics in Corpus Linguistics: A Practical Guide by Publication Date: 2018Do you use language corpora in your research or study, but find that you struggle with statistics? This practical introduction will equip you to understand the key principles of statistical thinking and apply these concepts to your own research, without the need for prior statistical knowledge.
Statistical Methods in Language and Linguistic Research by Publication Date: 2013The aim of this book is to illustrate with numerous examples how quantitative methods can fruitfully contribute to linguistic analysis and research. The book attempts to present mathematical and statistical properties of natural languages and introduces some of the quantitative methods which are most valuable in empirical work with texts and corpora.
R Open Source Statistical Software
The R software is frequently used by linguists for data analysis. Below are some books that look at the exploration and analysis of linguistic data using R.
R is open source and freely available for download for UNIX, Windows and MacOS platforms at The R Project for Statistical Computing site. You can also download RStudio, which includes a code editor, debugging and visualization tools.
Statistics for Linguists: An Introduction Using R by Publication Date: 2019This is the first statistics textbook on linear models for linguistics. The book covers simple uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive mathematical details.
Corpus Linguistics and Statistics with R: Introduction to Quantitative Methods in Linguistics by Publication Date: 2017The statistical methodology and R-based coding teaches readers the basic and then more advanced skills to work with large data sets in their linguistics research and studies. 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.
Quantitative Corpus Linguistics with R: A Practical Introduction (2nd ed.) by Publication Date: 2017This book 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 (particularly corpus linguists), this book is hands-on and leads the reader through dozens of small applications as well as larger case studies.
How to Do Linguistics with R: Data exploration and statistical analysis by Publication Date: 2015This book provides linguists with a statistical toolkit for exploration and analysis of linguistic data. It employs R, a free software environment for statistical computing, which is increasingly popular among linguists.
Statistics for Linguistics with R: A Practical Introduction by Publication Date: 2009This book is an introduction to statistics for linguists using the open source software R. It is aimed at students and instructors/professors with little or no statistical background and is written in a non-technical and reader-friendly/accessible style.
Analyzing Linguistic Data: A Practical Introduction to Statistics Using R by Publication Date: 2008Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. 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.
