Data Analysis

Bibliography of Research Methods TextsACRL IS Research and Scholarship Committee


The book of R : a first course in programming and statisticsDavies, Tilman M. 2016. The Book of R: A First Course in Programming and Statistics. San Francisco: No Starch Press. 832p. ISBN: 1593276516.

The promise of R is huge: a free, open-source statistical analysis program with powerful packages for beautiful visualizations. Yet, with its no-frills command-line interface, many find R to be a challenging tool to learn. This text starts with helpful, step-by-step instructions for downloading the R software and selecting the initial packages to install (a slightly daunting task for the inexperienced). From the start, the text integrates helpful best practices that contribute to the R coding community and to building an easily understood coding style. Divided into five parts, the book begins with foundational programming syntax, builds on structures and common statements for programming, then shifts to statistics and probability, with a focus on descriptive statistics and common visualizations, followed by a section on statistical tests and models, and finally a unit on using advanced graphics in R.  The book introduces statistical concepts, (such as types of variables) alongside the statistical analysis concepts, and includes short practice exercises throughout. A companion website also has downloadable practice files. With its thorough build-up of concepts and straightforward explanations, this would be a useful self-study text for those who could commit to learning R a few hours each week or as a reference work for those with a little prior experience.

Joe Goetz and Lindsay Roberts, 2017

Qualitative data analysis : an introductionGrbich, Carol. 2013. Qualitative Data Analysis: An Introduction. 2nd ed. Thousand Oaks, CA: SAGE. 344p. ISBN: 9781446202975.

The second edition of Qualitative Data Analysis: An Introduction includes expanded coverage of important issues in qualitative data analysis as well as detailed examinations of old and new analytical approaches. The book is broken down into six parts: “General Approaches to Collecting and Analyzing Qualitative Data,” “Traditional Analytical Approaches,” “Newer Qualitative Approaches,” “Analytic Approaches for Existing Documentation,” “Data Management Using Qualitative Computer Programs,” and “Interpreting and Presenting Qualitative Data.” Grbich offers a general overview of data analysis in qualitative research, in-depth exploration of analytical approaches including grounded theory; classical, existential and hermeneutic phenomenology; feminist research including memory work; semiotic, structural and post-structural analyses; as well as newer qualitative approaches such as classical, auto- and cyberethnography as well as ethnodrama; content, narrative, conversation and discourse analysis; and visual interpretation.  The book is well balanced and contains ample examples, a glossary of terms, lists for further reading, and a bibliography. The writing is fluid and easy to understand for the novice as well as the experienced researcher.

– Leslie Ross, 2017

Practical statistics : a quick and easy guide to IBM SPSS statistics, STATA, and other statistical softwareKremelberg, David. 2011. Practical Statistics: A Quick and Easy Guide to IBM® SPSS® Statistics, STATA, and Other Statistical Software. Thousand Oaks, CA: SAGE. 513p. ISBN: 1412974941.

Have you collected data and now need to know which tests are appropriate to perform and how to perform them? This valuable text covers two major statistical software platforms, SPSS and STATA, and focuses on what readers need to know in order to perform statistical tests quickly, rather than slowly building a foundation of statistical concepts. The author makes no assumptions for prior statistical knowledge and writes in an approachable, conversational tone. Topics covered include descriptive statistics, commonly used procedures such as correlation coefficients, Chi-Square, t-test, and ANOVA, linear and more advanced forms of regression, factor analysis, time-series analysis, and hierarchical and linear modeling, as well as commonly used visualizations, such as scatterplots, histograms, and the like. There is also an early chapter covering basics for creating and saving data sets in both SPSS and STATA, with screenshots. This basic software coverage is useful, though a software-specific text would be a helpful companion for more in-depth learning of these two software packages, especially for deeper learning of command-line syntax in STATA. The subsequent chapters follow a similar format with a general introduction to the test and theoretical background with straightforward, realistic examples, followed by an SPSS section and a STATA section with subsections that describe procedures and outputs through menus and screenshots as well as syntax, a particularly helpful feature for readers. A companion website includes downloadable datasets for each chapter to follow along with the exercises in the book, if desired. This text is an approachable and useful start to statistics and statistical software. It would be helpful in addition to a more in-depth, software-specific text, or as a refresher for someone who has taken a statistics course.

Lindsay Roberts, 2017

Krippendorff, Klaus. 2004. Content Analysis: An Introduction to its Methodology2nd ed. Thousand Oaks, CA: Sage Publications, Inc. xxiii, 413p. ISBN: 0761915451.

A substantive exploration of content analysis, its procedures and protocols, this very thorough text will be usefully considered by librarians seeking to explore the behavior, attitudes, and opinions of library users by “analyzing meaningful matter, texts, images, and voices” that is, data whose physical manifestations are secondary to what they mean to particular populations of people” (xxii).

While advanced and graduate students in social science disciplines are the primary, intended audience of this textbook, the effective introduction suggests different starting points for other users. Likewise, the pragmatic Chapter 14 is a practice-oriented summary of concepts previously presented and will serve readers as an overview and a quick pointer to more detailed discussion in earlier chapters. This edition is a comprehensive revision of the first and an extensive text; bold subheadings and Chapter 14 will particularly help practitioners use this text for select, pragmatic reading, while others will appreciate the full scope of this detailed discussion of content analysis.

Merinda McLure, March 2006

Qualitative data analysis : a methods sourcebookMiles, Matthew B., A. Michael Huberman, and Johnny Saldaña. 2014. Qualitative Data Analysis: A Methods Sourcebook. 3rd ed. Thousand Oaks, CA: SAGE. 381p. ISBN: 9781452257877.

Miles and Huberman’s classic research methods text Qualitative Data Analysis: An Expanded Sourcebook has been updated and expanded to become Qualitative Data Analysis: A Methods Sourcebook. Author Johnny Saldaña (The Coding Manual for Qualitative Researchers) joined Miles and Huberman to reorganize the existing content and improve the readability of the text. The third edition covers fundamentals of research design and data management, and original research studies are augmented by new examples from Saldaña’s recent qualitative work. This new edition retains the comprehensive and authoritative qualities of earlier editions but is vastly improved by updated content and Saldana’s contributions, which combine to make Qualitative Data Analysis an excellent text for qualitative researchers.

Leslie Ross, 2017

The ESRI Guide to GIS AnalysisMitchell, Andy. 1999. The ESRI Guide to GIS Analysis. Vol. 1: Geographic Patterns & Relationships. New York: ESRI Press. 186p. ISBN: 1879102064.

From ESRI, the company behind the ArcGIS software and the Story Maps tool, this guide to GIS analysis remains relevant despite its age through a focus on principles of analysis rather than details of any particular software. For example, displaying too many color categories in a map will confuse viewers, while using too few can leave out crucial information; the maximum number of categories seems to be six or seven. The book is full of brief, clearly titled informative sections with multiple color illustrations on virtually every page. This book is the first of three volumes; vol. 2 was published in 2009 and vol. 3 in 2012.

Joe Goetz, 2017

Handling qualitative data : a practical guideRichards, Lyn. 2015. Handling Qualitative Data: A Practical Guide. Thousand Oaks, CA: SAGE. 264p. ISBN: 9781446276068.

In the introduction of the third edition of Handling Qualitative Data: A Practical Guide, Richards states that since the first and second editions were published, “The popularity of qualitative methods has soared, in an ever widening range of disciplines, But…little has changed for embattled novice researchers meeting qualitative data before they have training in techniques for handling such records. This book was written for them” (p.1).  The book provides an introduction to qualitative research for students and practitioners and outlines a three step approach to help them to understand the processes, methodologies, and issues that are central to qualitative research. The three steps or parts of Richard’s process are “Setting Up,” which includes creating and recording data; “Working with the Data,” which includes coding and handling ideas; and “Making Sense of Your Data,” which includes defining what you are looking for, seeing it, and successfully telling the story of what you found. Recommended as a clear, practical guide for novice researchers.

Leslie Ross, 2017

The coding manual for qualitative researchersSaldaña, Johnny. 2016. The Coding Manual for Qualitative Researchers. 3rd ed. Thousand Oaks, CA: SAGE. 368p. ISBN: 1473902495.

Intended as a reference work, this book focuses specifically on coding methods for analyzing many, though not all, types of qualitative data. The book highlights 33 coding methods as examples for a variety of project types. Chapters offer an introduction to qualitative coding and take readers through first and second cycle coding methods and transitioning from coding to writing up the research. Sections also focus on solo and team coding and coding by hand or with software, though the book does not provide detailed help with any one specific software. This is a practical and approachable text for learning about or refining coding skills. A companion website includes a helpful list of well-known qualitative data analysis software, downloadable data for practicing coding, and a list of sample articles that illustrate coding methods described in the text.

Lindsay Roberts, 2017

Statistics for people who (think they) hate statistics : Using excel 2016Salkind, Neil. 2016. Statistics for People Who (Think They) Hate Statistics: Using Excel 2016. 4th ed. Thousand Oaks, CA: SAGE. 512p. ISBN: 1483374084.

Limiting itself to Microsoft Excel and assuming a complete beginner as its reader, this book provides an outstanding step-by-step introduction to practical statistical analysis while requiring a minimal output of resources. For librarians who want to learn statistics on the job, Salkind’s book provides authoritative and clear explanations of the basic tests and procedures. Other editions of the book use SPSS or previous versions of Excel.

Joe Goetz, 2017

Using software in qualitative research : a step-by-step guideSilver, Christina, and Ann Lewins. 2014. Using Software in Qualitative Research: A Step-by-Step Guide. Thousand Oaks, CA: SAGE. 355p. ISBN: 1446249727.

While giving thorough coverage of several software tools for analysis of qualitative research data, this book also takes a valuable step back, putting the use of the software in a larger context of writing, thinking and interpretation. Computer Assisted Qualitative Data Analysis (CAQDAS) packages described include ATLAS.ti, DEDOOSE, HyperRESEARCH, MAXQDA, NVivo, QDA Miner, and Transana. A companion website includes step-by-step tutorials for all seven software packages.

Joe Goetz, 2017


Return to Bibliography of Research Methods Texts Main Page