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Two Introductory Texts on Using Statistics for Linguistic Research and Two Books Focused on Theory

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1. General The four books discussed in this section can be broadly divided into two groups: two introductory texts on using statistics for linguistic research and two books focused on theory. Both Statistics for Linguists: A Step-by-Step Guide for Novices by David Eddington and How to do Linguistics with R: Data Exploration and Statistical Analysis by Natalia Levshina offer an introduction to statistics and, more specifically, how it can be applied to linguistic research. Covering the same basic statistical concepts and tests and including hands- on exercises with answer keys, the textbooks differ primarily in two respects: the choice of statistical software package (with subsequent differences reflecting this choice) and the scope of statistical tests and methods that each covers. Whereas Eddington’s text is based on widely used but costly SPSS and focuses on the most common statistical tests, Levshina’s text makes use of open-source software R and includes additional methods, such as Semantic Vector Spaces and making maps, which are not yet mainstream. In his introduction to Statistics for Linguists, Eddington explains choosing SPSS over R because of its graphical user interface, though he acknowledges that ‘in comparison to SPSS, R is more powerful, produces better graphics, and is free’ (p. xvi). This text is therefore more appropriate for researchers and students who are more comfortable with point-and-click computer programs and/or do not have time to learn to manoeuvre the command-line interface of R. Eddington’s book also has the goal of being ‘a truly basic introduction – not just in title, but in essence’ (p. xvi) and thus focuses on the most mainstream statistical tools available for linguistic analysis. This is reflected in the length of the book, which is divided into nine chapters: the first (‘Getting to Know SPSS’) introduces the reader to the basics of SPSS; the second (‘Descriptive and Inferential Statistics’) contains some of the basic concepts of statistics-based research, and the last seven chapters each focus on a particular statistical test (ch. 3, ‘Pearson Correlation’; ch. 4, ‘Chi-square’; ch. 5, ‘T-Test’; ch. 6, ‘ANOVA (Analysis of Variance)’; ch. 7, ‘Multiple Linear Regression’; ch. 8, ‘Mixed-Effects Models’; ch. 9, ‘Mixed- Effects Logistic Regression’). A number of hands-on exercises are included for practice, and readers are referred to the author’s website for answer keys and data sets for some of the exercises; it is odd, though, that these documents are not made available through the publisher’s website. Moreover, the webpage itself is quite basic, with a simple alphabetical list of the documents, which are not named for the relevant chapter, but it is still easy enough to access the necessary documents. Two nice features of the text are how chapters 3 to 9 start and end. Each chapter starts by clearly stating what kinds of questions the test can be used to answer and what kind of data is appropriate for the test – this makes it easy to use the book as a quick statistical reference. Moreover, near the end of each chapter, the author provides a ‘recipe’ for the statistical test – a step-by-step guide to the application of the statistical test. The lay-out of the text, however, is plain and at times a bit difficult to follow. Levshina’s How to do Linguistics with R not only offers an introduction to the more common statistical tests but also includes more specific linguistic approaches such as the measure of associations between words and constructions. It is divided into nineteen chapters that can be broadly divided into four parts. The preparatory section of the book includes chapter 1, which introduces statistics in research as well as some basic statistical concepts, and chapter 2, which provides a clear and gentle introduction to R, whose command-line interface might initially intimidate those with no or only a limited background in programming. The next two chapters continue with basic statistical concepts, including the first descriptive analysis of quantitative (chapter 3) and qualitative (chapter 4) variables. Chapters 5 through 14 explain the main statistical tests and analytical statistics: t-test (chapter 5), correlational analysis (chapter 6), linear regression (chapter 7), different types of ANOVA (chapter 8), various association measures (chapters 9-11), logistic regressions (chapters 12-13), and conditional inference trees and random forests (chapter 14). The final chapters focus on various exploratory multivariate methods: distributional approaches to semantics (chapters 15 and 16), Multidimensional Scaling (chapter 17), Principal Components Analysis and Factor Analysis (chapter 18), and Simple and Multiple Correspondence Analysis (chapter 19). All of the study questions and hands-on exercises with keys are available on a dedicated webpage through the publisher that is easy to access and navigate. Some useful features of the text are its lay-out and formatting (it includes blue textboxes with useful additional information that can be skipped, if necessary) and its description of how to report the various statistical tests in research – the information you should include for each test and a template for reporting the data. Evelien Keizer’s A Functional Discourse Grammar for English is the first textbook on Functional Discourse Grammar [FDG], a typologically based theory of language structure and the recent incarnation of and elaboration on Simon Dik’s Functional Grammar. Clearly and accessibly written, the book focuses on outlining FDG and showing how it can be used to analyse the most important grammatical features of PDE while also including several examples from various languages so as not to lose sight of FDG’s typological orientation. Keizer presents the theory in a detailed and structured way over its seven chapters. Chapter 1 (‘Why Functional Discourse Grammar?’) introduces the basics of linguistic theory in general, contrasting functional and formal approaches, before going into more detail about FDG specifically, including the relevance of each of the components of the name to the theory and its underlying assumptions. Chapter 2 (‘The general architecture of FDG’) briefly outlines the basic concepts of FDG and its hierarchical structure. The four levels of representation are each fleshed out in the following chapters 3 to 6: ‘The Interpersonal Level’, ‘The Representational Level’, ‘The Morphosyntactic Level’, and ‘The Phonological Level’. Three concrete and elaborated applications of the theory to analyses of sentences in English are demonstrated in chapter 7 ‘Sample Representations’. Each chapter includes short questions throughout that engage the student while reading and ends with exercises that challenge students to apply the theory to new data. Edited by Jonathan J. Webster, The Bloomsbury Companion to M. A. K. Halliday is a collection of essays exploring the life, influences, and theory of Halliday, the founder of Systemic Functional Linguistics [SFL]. Aimed at a professional audience, this comprehensive volume contains nineteen contributions divided into four sections representing different periods in Halliday’s life and the development of his theory of language. The single essay in Part I (‘Halliday’s Life’) by Jonathan J. Webster begins the entire collection by succinctly outlining Halliday’s life in a brief biography. Part II (‘Halliday: The Making of a Mind’) includes five chapters, each of which deals with a particular influence that shaped Halliday and his ideas about language, ranging from politics (‘The Influence of Marxism’ by M. A. K. Halliday), to general trends in science (‘The “History of Ideas” and Halliday’s Natural Science of Meaning’ by David G. Butt), to more specific linguistic influences (‘Halliday in China: Legacies and Advances from LUO, WANG and Beyond’ by Peng Xuanwei; ‘“Socially Realistic Linguistics”: The Firthian Tradition’ by Braj B. Kachru; ‘Systemic Functional Linguistics: Halliday and the Evolution of a Social Semiotic’ by Ruqaiya Hasan). The eight chapters in Part III (‘Halliday: Ideas about Language’) examine in more detail various phenomena that Halliday has explored through the lens of his theory, re- inforcing how strongly grounded in language use his theory is. The two chapters by Christian M.I.M. Matthiessen, ‘Halliday on Language’ and ‘Halliday’s Conception of Language as a Probabilistic System’, lay down the basics of SFL and elaborates more fully on Halliday’s idea of language as a probabilistic system. ‘Language Development in Early Childhood: Learning How to Mean’ by Jane Torr outlines Halliday’s research into child language development, primarily based on a detailed analysis of his son Nigel’s linguistic transition. J.R. Martin offers an introduction to Halliday’s view on grammar from a pedagogical perspective in ‘Halliday the Grammarian: Axial Foundations’. In ‘Intonation’, Bradley A. 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