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It compares David Eddington’s SPSS-based step-by-step approach with Natalia Levshina’s R-based data exploration and analysis, highlighting differences in software choice, covered tests, exercises, and usability features. It also reviews Evelien Keizer’s Functional Discourse Grammar for English as a structured FDG theory guide, explaining its chapter-based progression and analytic purpose.",{"@graph":63,"@context":110},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/introduction-to-statistics-and-theory-in-linguistic-research-two-introductory-and-two-theory-textbooks/171588/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/introduction-to-statistics-and-theory-in-linguistic-research-two-introductory-and-two-theory-textbooks/171588.png","ImageObject",442,249,{"name":88,"@type":89},"Maya Linwood","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/vnd.openxmlformats-officedocument.wordprocessingml.document","2026-09-22","2026-09-01",true,{"@type":98,"interactionType":99,"userInteractionCount":76},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104],{"name":105,"@type":106,"acceptedAnswer":107},"What is the main focus of Keizer’s A Functional Discourse Grammar for English?","Question",{"text":108,"@type":109},"It presents Functional Discourse Grammar (FDG) as a typologically based theory and shows how to analyze key grammatical features of contemporary English using a structured, example-rich chapter sequence.","Answer","https://schema.org",{"og:url":78,"og:type":112,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":114,"canonical":78},"index,follow",{"doc_id":116,"site_id":56},171588,1790038502,{"code":4,"msg":5,"data":119},{"doc_id":116,"user_id":120,"nickname":88,"user_avatar":121,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":122,"file_id":123,"file_url":124,"file_type":125,"file_size":126,"view_count":127,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":128,"language":129,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":130,"faqs":131,"seo_title":132,"seo_description":61,"update_tm":133,"read_time":134},962084928432,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","1. General\nThe 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.\nBoth 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.\nIn 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.\nLevshina’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 statis","cbCaivkzDTAwMwZv","https://ap.wps.com/l/cbCaivkzDTAwMwZv","docx",321142,6,138,"English","# Textbook group overview\n## Statistics-focused introductory texts\n### SPSS-based: key structure and chapter coverage\n### R-based: tests, methods, and learning supports\n## Theory-focused text\n### Functional Discourse Grammar for English","[{\"question\":\"What is the main focus of Keizer’s A Functional Discourse Grammar for English?\",\"answer\":\"It presents Functional Discourse Grammar (FDG) as a typologically based theory and shows how to analyze key grammatical features of contemporary English using a structured, example-rich chapter sequence.\"}]","Introduction to Statistics and Theory in Linguistic Research - Two Introductory and Two Theory Textbooks | DOCX",1788284262,48]