Storytelling with Data


Book Description

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!




Show Me the Data!


Book Description

Data collection is one of the critical elements of an effective, efficient, and accountable program that supports student development and learning. However, many intervention teams struggle to develop reasonable and sustainable methods of gathering information about student performance and progress. Now comes SHOW ME THE DATA! This must-have resource consists of a brief discussion on data collection accompanied by a CD containing a comprehensive compilation of data sheets to help make that once-dreaded task easier and simpler.




Show Me the Data


Book Description

This lined notebook makes the perfect gift for data nerds, scientists, analysts, engineers, mathematicians, STEM students and programmers. 6x9 inches 110 pages Lined White paper Matte-finished cover




Dear Data


Book Description

Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.




Data Feminism


Book Description

A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.




Wake Me Up When the Data Is Over


Book Description

This book includes real-life examples from over 70 respected organizations, small and large, representing a multitude of industries using stories to drive results. Leaders from organizations such as Microsoft, Lands’ End, Verizon, U.S. Air Force, and World Vision demonstrate the strong positive influence stories can have. No abstract theories or platitudes are conveyed here. The book spells out how Kevin Roberts, CEO worldwide of Saatchi & Saatchi, achieved sustained sales growth after several mergers and downsizings caused the organization to fall on hard times. It also shows how Erik Shaw, president and CEO of FivePoint Federal Credit Union, overcame resistance to an organizational name change, resulting in membership growth exceeding the national average.




Invisible Women


Book Description

The landmark, prize-winning, international bestselling examination of how a gender gap in data perpetuates bias and disadvantages women. #1 International Bestseller * Winner of the Financial Times and McKinsey Business Book of the Year Award * Winner of the Royal Society Science Book Prize Data is fundamental to the modern world. From economic development to health care to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, because it treats men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this insidious bias: in time, in money, and often with their lives. Celebrated feminist advocate Caroline Criado Perez investigates this shocking root cause of gender inequality in Invisible Women. Examining the home, the workplace, the public square, the doctor’s office, and more, Criado Perez unearths a dangerous pattern in data and its consequences on women’s lives. Product designers use a “one-size-fits-all” approach to everything from pianos to cell phones to voice recognition software, when in fact this approach is designed to fit men. Cities prioritize men’s needs when designing public transportation, roads, and even snow removal, neglecting to consider women’s safety or unique responsibilities and travel patterns. And in medical research, women have largely been excluded from studies and textbooks, leaving them chronically misunderstood, mistreated, and misdiagnosed. Built on hundreds of studies in the United States, in the United Kingdom, and around the world, and written with energy, wit, and sparkling intelligence, this is a groundbreaking, highly readable exposé that will change the way you look at the world.




Restricted Data


Book Description

"Nuclear weapons, since their conception, have been the subject of secrecy. In the months after the dropping of the atomic bombs on Hiroshima and Nagasaki, the American scientific establishment, the American government, and the American public all wrestled with what was called the "problem of secrecy," wondering not only whether secrecy was appropriate and effective as a means of controlling this new technology but also whether it was compatible with the country's core values. Out of a messy context of propaganda, confusion, spy scares, and the grave counsel of competing groups of scientists, what historian Alex Wellerstein calls a "new regime of secrecy" was put into place. It was unlike any other previous or since. Nuclear secrets were given their own unique legal designation in American law ("restricted data"), one that operates differently than all other forms of national security classification and exists to this day. Drawing on massive amounts of declassified files, including records released by the government for the first time at the author's request, Restricted Data is a narrative account of nuclear secrecy and the tensions and uncertainty that built as the Cold War continued. In the US, both science and democracy are pitted against nuclear secrecy, and this makes its history uniquely compelling and timely"--




R for Data Science


Book Description

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results




Envisioning Information


Book Description

Escaping flatland -- Micro/macro readings -- Layering and separation -- Small multiples -- Color and information -- Narratives and space and time -- Epilogue.