Data Literacy Fundamentals


Book Description

The vast majority of people in the world today do not receive a formal education that adequately prepares them for the level of data literacy required of them in their careers and by their communities. As a result, many are being left behind by the transition to data-driven dialogues and decisions all around them, and they're seeking ways to break down the barriers that are preventing them from participating. Data Literacy Fundamentals covers foundational topics such as the overall goal of data, various ways of measuring and categorizing the world, five different forms of data analysis and when they apply, pros and cons related to how we display data in tabular or graphic form, and the way teams work together to convert data into insight.This book has been written for anyone who is just getting started with data and who wants to feel more confident in their understanding of what it is, what it isn't, and what it's used for. This invaluable resource will cure you of your "dataphobia", teach you the basic concepts of data, and set you on a path of learning that will ultimately result in fluency in the language of data.




The Basics of Data Literacy


Book Description

Here's the ideal statistics book for teachers with no statistical background. Written in an informal style with easy-to-grasp examples, The Basics of Data Literacy teaches you how to help your students understand data. Then, in turn, they learn how to collect, summarize, and analyze statistics inside and outside the classroom. The books 10 succinct chapters provide an introduction to types of variables and data, ways to structure and interpret data tables, simple statistics, and survey basics from a student perspective. The appendices include hands-on activities tailored to middle and high school investigations. Because data are so central to many of the ideas in the Next Generation Science Standards, the ability to work with such information is an important science skill for both you and your students. This accessible book will help you get over feeling intimidated as your students learn to evaluate messy data on the Internet, in the news, and in future negotiations with car dealers and insurance agents.




Learning to See Data


Book Description

This book is associated with the 'Data Literacy Level 1' on-demand online course: https://dataliteracy.com/courses/data-literacy-level-1 For most of us, it's rare to go a full day without coming across data in the form of a chart, map or dashboard. Graphical displays of data are all around us, from performance indicators at work to election trackers on the news to traffic maps on the road. But few of us have received training or instruction in how to actually read and interpret them. How many times have we been misled simply because we aren't aware of the pitfalls to avoid when interpreting data visualizations. Learning to See Data will teach you the different ways that data can be encoded in graphical form, and it will give you a deeper understanding of the way our human visual system interprets these encodings. You will also learn about the most common chart types, and the situations in which they are most appropriate. From basic bar charts to overused pie charts to helpful maps and many more, a wide array of chart types are covered in detail, and conventions, pitfalls, strengths and weaknesses of each of them are revealed. This book will help you develop fluency in the interpretation of charts, an ability that we all need to hone and perfect if we are to make meaningful contributions in the professional, public and personal arenas of life. The principles covered in it also serve as a critical background for anyone looking to create charts that others will be able to understand. "This book is clear and evocative, thorough and thoughtful, and remarkably readable: a marvelous launchpad into the world of data." –Tamara Munzner, Professor, University of British Columbia Computer Science "Everyone of us needs good data literacy skills to survive in the modern world. Without them, it's hard to succeed at work, or survive the onslaught of information (and misinformation) across all our media. Ben's book provides the necessary building blocks for a strong foundation. From that foundation, Ben's approach will inspire you to own the process of developing your skills further." –Andy Cotgreave, Technical Evangelism Director, Tableau




Data Literacy


Book Description

A practical, skill-based introduction to data analysis and literacy We are swimming in a world of data, and this handy guide will keep you afloat while you learn to make sense of it all. In Data Literacy: A User's Guide, David Herzog, a journalist with a decade of experience using data analysis to transform information into captivating storytelling, introduces students and professionals to the fundamentals of data literacy, a key skill in today’s world. Assuming the reader has no advanced knowledge of data analysis or statistics, this book shows how to create insight from publicly-available data through exercises using simple Excel functions. Extensively illustrated, step-by-step instructions within a concise, yet comprehensive, reference will help readers identify, obtain, evaluate, clean, analyze and visualize data. A concluding chapter introduces more sophisticated data analysis methods and tools including database managers such as Microsoft Access and MySQL and standalone statistical programs such as SPSS, SAS and R.




Avoiding Data Pitfalls


Book Description

Avoid data blunders and create truly useful visualizations Avoiding Data Pitfalls is a reputation-saving handbook for those who work with data, designed to help you avoid the all-too-common blunders that occur in data analysis, visualization, and presentation. Plenty of data tools exist, along with plenty of books that tell you how to use them—but unless you truly understand how to work with data, each of these tools can ultimately mislead and cause costly mistakes. This book walks you step by step through the full data visualization process, from calculation and analysis through accurate, useful presentation. Common blunders are explored in depth to show you how they arise, how they have become so common, and how you can avoid them from the outset. Then and only then can you take advantage of the wealth of tools that are out there—in the hands of someone who knows what they're doing, the right tools can cut down on the time, labor, and myriad decisions that go into each and every data presentation. Workers in almost every industry are now commonly expected to effectively analyze and present data, even with little or no formal training. There are many pitfalls—some might say chasms—in the process, and no one wants to be the source of a data error that costs money or even lives. This book provides a full walk-through of the process to help you ensure a truly useful result. Delve into the "data-reality gap" that grows with our dependence on data Learn how the right tools can streamline the visualization process Avoid common mistakes in data analysis, visualization, and presentation Create and present clear, accurate, effective data visualizations To err is human, but in today's data-driven world, the stakes can be high and the mistakes costly. Don't rely on "catching" mistakes, avoid them from the outset with the expert instruction in Avoiding Data Pitfalls.




Data Literacy Fundamentals


Book Description

The vast majority of people in the world today do not receive a formal education that adequately prepares them for the level of data literacy required of them in their careers and by their communities. As a result, many are being left behind by the transition to data-driven dialogues and decisions all around them, and they're seeking ways to break down the barriers that are preventing them from participating. Data Literacy Fundamentals covers foundational topics such as the overall goal of data, various ways of measuring and categorizing the world, five different forms of data analysis and when they apply, pros and cons related to how we display data in tabular or graphic form, and the way teams work together to convert data into insight. This book has been written for anyone who is just getting started with data and who wants to feel more confident in their understanding of what it is, what it isn't, and what it's used for. This invaluable resource will cure you of your "dataphobia", teach you the basic concepts of data, and set you on a path of learning that will ultimately result in fluency in the language of data.




EDF Data Literacy Professional Courseware


Book Description

In order to leverage data, decision makers and management have to base their decisions on the vast amounts of information being collected and generated nowadays. Understanding data requires a set of skills that are easy to learn, but in general are far from intuitive. None of us are born with the capacity to understand data: it is a human abstract construct, so we all need to learn how to work with it. How data can be leveraged, what the common pitfalls are and how data can often be misinterpreted are all crucial pieces of knowledge for all modern business professionals, particularly those in management. It is a misconception that humans no longer have a role to play and that data can make the decisions for us. However, in the foreseeable future, data-guided decisions will be the norm rather than the exception. The EDF Certification recognizes the awareness and understanding of the components of data literacy and how to foster its adoption and application for the benefit of everybody who needs to make decisions based on data. The EDF Certification is achieved through an exam which demonstrates that a participant: Understands what data is and isn’t; Is aware of the questions that need answered whenever you receive some data; Understands how to summarize data in the correct way; Is aware of the main processes involved from data origins through to usage; Understands what data quality is; Understands how to use data in order to measure performance; Is aware of the impact of our expectations on data analysis; Understands the main human biases involved in data analysis; Is aware of the principal types of data analysis; Understands the impact of context on analysis; Understands how to apply storytelling principles to data arguments.




Data Literacy Practitioner's Guide


Book Description

As kids, we learned our native language: reading, writing, and speaking. You learn a language by starting with grammar, trying it out, making mistakes and improving it. We are flooded with facts and figures daily, but how well do we understand the meaning behind all those numbers? How can we turn this data into value in our day-to-day work and for the organization we work for? The ability to derive meaningful information from data is called Data Literacy. Making sense of data is no longer just a skill for data scientists and technology experts but an essential skill for all of us. Data Literacy is the ability to read, work with, analyze and argue with data. This course is the first step to make you aware of Data Literacy (as an essential skill) and how it impacts your work. You’ll learn the fundamentals and how they relate to working in a data-informed organization. This will be enough for some people to raise the required questions when confronted with data. For others, this is the first step in becoming a fluent data speaker. This Data Literacy Practitioner's Guide consist of four modules, each with its own weight towards the EDF Data Literacy Professional certification exam: Weight Topic Introduction Introduction to Data Literacy Read data 25% The ability to read and interpret data correctly. Which questions we need to ask to avoid fooling ourselves. Work with data 25% What happens to data during its journey from the source to final consumption? How does this impact the understanding and possibilities of this data? Analyze data 25% Data needs to be analyzed, not only read. In this section we’ll have a closer look at how we analyze data. Argue with data 25% Once we have found interesting insights in the data, we need to share this with our audience. In this part we’ll look at what we need to do so our audience understands the data in the best possible way.




Proceedings of the 3rd International and Interdisciplinary Conference on Image and Imagination


Book Description

This book gathers peer-reviewed papers presented at the 3rd International and Interdisciplinary Conference on Image and Imagination (IMG), held in Milano, Italy, in November 2021. Highlighting interdisciplinary and multi-disciplinary research concerning graphics science and education, the papers address theoretical research as well as applications, including education, in several fields of science, technology and art. Mainly focusing on graphics for communication, visualization, description and storytelling, and for learning and thought construction, the book provides architects, engineers, computer scientists, and designers with the latest advances in the field, particularly in the context of science, arts and education.