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Data Literacy Fundamentals

Author : Ben Jones

Publisher :

Page : pages

File Size : 16,38 MB

Release : 2020-07-03

Category :

ISBN : 9781733263429

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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

Author : Michael Bowen

Publisher :

Page : 171 pages

File Size : 30,35 MB

Release : 2014

Category : Graphic methods

ISBN : 9781938946035

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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

Author : Ben Jones

Publisher : Data Literacy Press

Page : 1 pages

File Size : 22,5 MB

Release : 2020-12-15

Category : Business & Economics

ISBN : 1733263454

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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

Author : David Herzog

Publisher : SAGE Publications

Page : 240 pages

File Size : 13,67 MB

Release : 2015-01-29

Category : Language Arts & Disciplines

ISBN : 1483378675

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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.



Data Literacy Fundamentals

Author : Ben Jones

Publisher : Data Literacy Press

Page : 132 pages

File Size : 45,29 MB

Release : 2020-07-03

Category : Business & Economics

ISBN : 1733263438

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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.



Avoiding Data Pitfalls

Author : Ben Jones

Publisher : John Wiley & Sons

Page : 272 pages

File Size : 21,27 MB

Release : 2019-11-19

Category : Business & Economics

ISBN : 1119278163

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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.



Fundamentals of Literacy Instruction & Assessment, Pre-K-6

Author : Martha Clare Hougen

Publisher : Brookes Publishing Company

Page : 416 pages

File Size : 23,52 MB

Release : 2020

Category : Language arts (Early childhood)

ISBN : 9781681253756

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Book Description

"This core text introduces pre-service teachers to the essential components of literacy and describes how to effectively deliver explicit, evidence-based instruction on each component"--



Storytelling with Data

Author : Cole Nussbaumer Knaflic

Publisher : John Wiley & Sons

Page : 284 pages

File Size : 33,43 MB

Release : 2015-10-09

Category : Mathematics

ISBN : 1119002265

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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!



Tableau Prep: Up & Running

Author : Carl Allchin

Publisher : O'Reilly Media

Page : 444 pages

File Size : 28,93 MB

Release : 2020-08-03

Category : Computers

ISBN : 1492079596

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Book Description

For self-service data preparation, Tableau Prep is relatively easy to use—as long as you know how to clean and organize your datasets. Carl Allchin, from The Information Lab in London, gets you up to speed on Tableau Prep through a series of practical lessons that include methods for preparing, cleaning, automating, organizing, and outputting your datasets. Based on Allchin’s popular blog, Preppin’ Data, this practical guide takes you step-by-step through Tableau Prep’s fundamentals. Self-service data preparation reduces the time it takes to complete data projects and improves the quality of your analyses. Discover how Tableau Prep helps you access your data and turn it into valuable information. Know what to look for when you prepare data Learn which Tableau Prep functions to use when working with data fields Analyze the shape and profile of your dataset Output data for analysis and learn how Tableau Prep automates your workflow Learn how to clean your dataset using Tableau Prep functions Explore ways to use Tableau Prep techniques in real-world scenarios Make your data available to others by managing and documenting the output



R for Data Science

Author : Hadley Wickham

Publisher : "O'Reilly Media, Inc."

Page : 521 pages

File Size : 11,44 MB

Release : 2016-12-12

Category : Computers

ISBN : 1491910364

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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