Overview

""This is an important book on an important topic. I particularly like the examples showing different visualizations of the same data and the parallel presentation of graphics and code. And I absolutely love the chapter on visual storytelling. I can't wait to use this book in my classes.""- Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University, New York ""A book that gives learners the inspiration, knowledge and worked examples to create cutting edge visualisations of their own.""- James Chesire, Professor of Geographic Information and Cartography, University College London Visualization for Social Data Science provides end-to-end skills in visual data analysis. The book demonstrates how data graphics and modern statistics can be used in tandem to process, explore, model and communicate data-driven social science. It is packed with detailed data analysis examples, pushing you to do visual data analysis. As well as introducing, and demonstrating with code, a wide range of data visualizations for exploring patterns in data, Visualization for Social Data Science shows how models can be integrated with graphics to emphasise important structure and de-emphasise spurious structure and the role of data graphics in scientific communication -- in building trust and integrity. Many of the book’s influences are from data journalism, as well as information visualization and cartography. Each chapter introduces statistical and graphical ideas for analysis, underpinned by real social science datasets. Those ideas are then implemented via principled, step-by-step, workflows in the programming environment R. Key features include: • Extensive real-world data sets and data analysis scenarios in Geography, Public Health, Transportation, Political Science; • Code examples fully-integrated into main text, with code that builds in complexity and sophistication; • Quarto template files for each chapter to support literate programming practices; • Functional programming examples, using tidyverse, for generating empirical statistics (bootstrap resamples, permutation tests) and working programmatically over model outputs; • Unusual but important programming tricks for generating sophisticated data graphics such as network visualizations, dot-density maps, OD maps, glyphmaps, icon arrays, hypothetical outcome plots and graphical line-ups plots. Every data graphic in the book is implemented via ggplot2. • Chapters on uncertainty visualization and data storytelling that are uniquely accompanied with detailed, worked examples.

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9781032259710

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Reviews

""This is an important book on an important topic. I particularly like the examples showing different visualizations of the same data and the parallel presentation of graphics and code. And I absolutely love the chapter on visual storytelling. I can't wait to use this book in my classes.""- Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University, New York ""A book that gives learners the inspiration, knowledge and worked examples to create cutting edge visualisations of their own.""- James Chesire, Professor of Geographic Information and Cartography, University College London ""This is a very well-structured, clearly-written introduction to visualizing social data, especially data with a strong spatial component. The examples are accessible, instructive, and beautifully developed within each chapter. While the book is an excellent introduction to methods and techniques, it never loses sight of why we want to look at data in the first place."" - Kieran Healy, Duke University ""If a picture is worth a thousand words, a book demonstrating the how and why of effective visualisation that complements and strengthens data analytics is priceless. Beecham’s volume is such a prize, pairing examples and applications from across the social sciences with code and data to illustrate the power of statistical and visual analysis working in tandem."" - Rachel Franklin, Executive Director, Center for Geographic Analysis, Harvard University ""Novel sources of “found” data are creating new opportunities and greater responsibilities for understanding data to avoid specious discoveries. Visualization for Social Data Science enables social scientists to be careful, thoughtful and effective social data scientists by illuminating both how and why to incorporate visualization into scientific discovery."" - Harvey J. Miller, Center for Urban and Regional Analysis, Ohio State University ""Balance is at the root of good design, and resonates throughout Visualization for Social Data Science. The book’s harmony of concepts and techniques, precision and creativity, provide a perfect tonic for any social scientist seeking to scale up their visualization and data science knowledge and skills."" - Matt Duckham, Director of Information in Society EIP, RMIT, Melbourne

""This is an important book on an important topic. I particularly like the examples showing different visualizations of the same data and the parallel presentation of graphics and code. And I absolutely love the chapter on visual storytelling. I can't wait to use this book in my classes.""- Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University, New York ""A book that gives learners the inspiration, knowledge and worked examples to create cutting edge visualisations of their own.""- James Chesire, Professor of Geographic Information and Cartography, University College London ""This is a very well-structured, clearly-written introduction to visualizing social data, especially data with a strong spatial component. The examples are accessible, instructive, and beautifully developed within each chapter. While the book is an excellent introduction to methods and techniques, it never loses sight of why we want to look at data in the first place."" - Kieran Healy, Duke University ""If a picture is worth a thousand words, a book demonstrating the how and why of effective visualisation that complements and strengthens data analytics is priceless. Beecham’s volume is such a prize, pairing examples and applications from across the social sciences with code and data to illustrate the power of statistical and visual analysis working in tandem."" - Rachel Franklin, Executive Director, Center for Geographic Analysis, Harvard University ""Novel sources of “found” data are creating new opportunities and greater responsibilities for understanding data to avoid specious discoveries. Visualization for Social Data Science enables social scientists to be careful, thoughtful and effective social data scientists by illuminating both how and why to incorporate visualization into scientific discovery."" - Harvey J. Miller, Center for Urban and Regional Analysis, Ohio State University

Author Information

Roger Beecham is Associate Professor of Visual Data Science at University of Leeds School of Geography and Director of Research & Innovation at Leeds Institute for Data Analytics. He has published award-winning methodological work in data visualization, statistical practice and applied social science. He has taught visual data analysis for many years – to undergraduate and postgraduate students, experienced academics and data analysis professionals.

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