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Trina Chiasson, Dyanna Gregory and Over 50 people worked hard over the course of many months to create this book, which we’re delighted to offer as a free resource. If you do use or build upon this work, make sure to give credit to the contributors who made it happen by including a link to infoactive.co/data-design.
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Data at Work by Jorge CamõesData at Work will help students to know which type of chart to use and how to format it, regardless of which spreadsheet application they use and whether or not they have any design experience. In this book, they'll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatterplots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant charts will be available online for students to download, with brief explanations of how they were created.
A fresh look at visualization from the author of Visualize This Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data. Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as well as from professionals in statistics, art, design, business, computer science, cartography, and more Examines standard rules across all visualization applications, then explores when and where you can break those rules Create visualizations that register at all levels, with Data Points: Visualization That Means Something.
Students and researchers across the social sciences
Presenting Data Effectively by Stephanie D. H. EvergreenFocusing on the guiding principles of presenting data in evidence-based ways so that audiences are effectively engaged and researchers are better understood, Evergreen's exciting new book offers the best communication strategies available to anyone working with data. Indeed, with this highly accessible step-by-step guide, anyone--from students developing a research poster for a school project to faculty and researchers presenting data findings at a conference--can learn how to present and communicate their research findings in more interesting and effective ways. Evergreen draws on her extensive experience in the study of research reporting, interdisciplinary evaluation, and data visualization, as well as from diverse interdisciplinary fields, including vision science, cognitive psychology, communications, and graphic design, to extract tangible and practical data-reporting communication lessons and insights. She then teaches readers how to apply those guiding principles to the design of data presentations to make it easier for the audience to understand, remember, and use data.Ancillaries * Link to the author′s blog and website * Selected chapter images in full colour * Research & Evaluation Report Layout Checklist * Templates of style sheets * Slide deck planning sheet * PowerPoint template illustrating the "Rule of Thirds" * Tips for applying guiding principles to other software programs
Call Number: P93.5 .E94 2014 (Fenwick Library)
Publication Date: 2013-10-04
Show Me the Numbers by Stephen FewAddressing the prevalent issue of poorly designed quantitative information presentations, this accessible, practical, and comprehensive guide teaches how to properly create tables and graphs for effective and efficient communication. The critical numbers that measure the health, identify the opportunities, and forecast the future of organizations are often misrepresented because few people are trained to design accurate, informative materials, but this manual helps put an end to misinformation. This revised edition of the highly successful book includes updated figures and 91 additional pages of content, including new chapters about quantitative narrative and current misuses of graphs—such as donut, circle, unit, and funnel charts—and new appendices that cover constructing table lens displays and box plots in Excel and useful color palettes for presentation materials.
Don't simply show your data--tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples--ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data--Storytelling with Data will give you the skills and power to tell it!
Storytelling with Data: Let's Practice by Cole Nussbaumer KnaflicInfluence action through data! This is not a book. It is a one-of-a-kind immersive learning experience through which you can become--or teach others to be--a powerful data storyteller. Let's practice! helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories. Expanding upon best seller storytelling with data's foundational lessons, Let's practice! delivers fresh content, a plethora of new examples, and over 100 hands-on exercises. Author and data storytelling maven Cole Nussbaumer Knaflic guides you along the path to hone core skills and become a well-practiced data communicator. Each chapter includes: ● Practice with Cole: exercises based on real-world examples first posed for you to consider and solve, followed by detailed step-by-step illustration and explanation ● Practice on your own: thought-provoking questions and even more exercises to be assigned or worked through individually, without prescribed solutions ● Practice at work: practical guidance and hands-on exercises for applying storytelling with data lessons on the job, including instruction on when and how to solicit useful feedback and refine for greater impact The lessons and exercises found within this comprehensive guide will empower you to master--or develop in others--data storytelling skills and transition your work from acceptable to exceptional. By investing in these skills for ourselves and our teams, we can all tell inspiring and influential data stories!
This book deals with the theory and practice in the design of data graphics and makes the point that the most effective way to describe, explore, and summarize a set of numbers is to look at pictures of those numbers, through the use of statistical graphics, charts, and tables. It includes 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Also offered is information on the design of the high-resolution displays, small multiples, editing and improving graphics, and the data-ink ratio. Time-series, relational graphics, data maps, multivariate designs, as well as detection of graphical deception: design variation vs. data variation, and sources of deception are discussed. Information on aesthetics and data graphical displays is included. The 2nd edition provides high-resolution color reproductions of the many graphics of William Playfair (1750-1800), adds color to other images where appropriate, and includes all the changes and corrections during the 17 printings of the 1st edition.
Better Data Visualizations - a Guide for Scholars, Researchers, and Wonks by Jonathan SchwabishNow more than ever, content must be visual if it is to travel far. Readers everywhere are overwhelmed with a flow of data, news, and text. Visuals can cut through the noise and make it easier for readers to recognize and recall information. Yet many researchers were never taught how to present their work visually. This book details essential strategies to create more effective data visualizations. Jonathan Schwabish walks readers through the steps of creating better graphs and how to move beyond simple line, bar, and pie charts. Through more than five hundred examples, he demonstrates the do's and don'ts of data visualization, the principles of visual perception, and how to make subjective style decisions around a chart's design. Schwabish surveys more than eighty visualization types, from histograms to horizon charts, ridgeline plots to choropleth maps, and explains how each has its place in the visual toolkit. It might seem intimidating, but everyone can learn how to create compelling, effective data visualizations. This book will guide you as you define your audience and goals, choose the graph that best fits for your data, and clearly communicate your message.
Publication Date: 2021-02-09
See also software-specific courses that cover data visualization (e.g., R, Python, Tableau, Excel).