America operates by ableist norms, which often silence or hide from view those with a disability. This book provides a platform or peek inside the lives of eight people with a disability, and it offers solutions for achieving access justice.
In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video. With Beautiful Data, you will: Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web Learn how to visualize trends in urban crime, using maps and data mashups Discover the challenges of designing a data processing system that works within the constraints of space travel Learn how crowdsourcing and transparency have combined to advance the state of drug research Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data Learn about the massive infrastructure required to create, capture, and process DNA data That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include: Nathan Yau Jonathan Follett and Matt Holm J.M. Hughes Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava Jeff Hammerbacher Jason Dykes and Jo Wood Jeff Jonas and Lisa Sokol Jud Valeski Alon Halevy and Jayant Madhavan Aaron Koblin with Valdean Klump Michal Migurski Jeff Heer Coco Krumme Peter Norvig Matt Wood and Ben Blackburne Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen Lukas Biewald and Brendan O'Connor Hadley Wickham, Deborah Swayne, and David Poole Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza Toby Segaran
The future of disability in America will depend on how well the U.S. prepares for and manages the demographic, fiscal, and technological developments that will unfold during the next two to three decades. Building upon two prior studies from the Institute of Medicine (the 1991 Institute of Medicine's report Disability in America and the 1997 report Enabling America), The Future of Disability in America examines both progress and concerns about continuing barriers that limit the independence, productivity, and participation in community life of people with disabilities. This book offers a comprehensive look at a wide range of issues, including the prevalence of disability across the lifespan; disability trends the role of assistive technology; barriers posed by health care and other facilities with inaccessible buildings, equipment, and information formats; the needs of young people moving from pediatric to adult health care and of adults experiencing premature aging and secondary health problems; selected issues in health care financing (e.g., risk adjusting payments to health plans, coverage of assistive technology); and the organizing and financing of disability-related research. The Future of Disability in America is an assessment of both principles and scientific evidence for disability policies and services. This book's recommendations propose steps to eliminate barriers and strengthen the evidence base for future public and private actions to reduce the impact of disability on individuals, families, and society.
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Applied regression and causal inference are central to statistics and data science. This book provides a large collection of stories, with hands-on activities, demonstrations, and problems that bring the subject to life and which facilitate group work and active student participation.
Communication Research Methods in Postmodern Culture explores communication research from a postmodern perspective while retaining key qualitative and quantitative research methods. The author uses easy-to-understand language to incorporate new research methods inspired by contemporary culture and includes review questions and suggested activities designed to help readers understand and master communication research. The blend of new and traditional methods creates a book appropriate to the study of communication in an increasingly complex cultural environment.
Influence 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!
In this fascinating follow-up to the bestselling Information is Beautiful and Knowledge is Beautiful, the king of infographics David McCandless uses spectacular visuals to give us all a bit of good news.
A concise and feisty takedown of the all-style, no-substance tech ventures that fail to solve our food crises. Why has Silicon Valley become the model for addressing today's myriad social and ecological crises? With this book, Julie Guthman digs into the impoverished solutions for food and agriculture currently emerging from Silicon Valley, urging us to stop trying to fix our broken food system through finite capitalistic solutions and technological moonshots that do next to nothing to actualize a more just and sustainable system. The Problem with Solutions combines an analysis of the rise of tech company solution culture with findings from actual research on the sector's ill-informed attempts to address the problems of food and agriculture. As this seductive approach continues to infiltrate universities and academia, Guthman challenges us to reject apolitical and self-gratifying techno-solutions and develop the capacity and willingness to respond to the root causes of these crises. Solutions, she argues, are a product of our current condition, not an answer to it.