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Explore three defining challenges that school teams face when gathering, interpreting, and utilizing school data. Complete with survey questions for efficient data collection, group work structures, strategies, and tools—along with essential definitions and descriptions of data types—this compelling guide will help you confront data obstacles and turn struggling committees into powerful communities of learners.
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!
A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.
Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.
Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.
INSTANT NEW YORK TIMES BESTSELLER “One of the most important books I’ve ever read—an indispensable guide to thinking clearly about the world.” – Bill Gates “Hans Rosling tells the story of ‘the secret silent miracle of human progress’ as only he can. But Factfulness does much more than that. It also explains why progress is so often secret and silent and teaches readers how to see it clearly.” —Melinda Gates "Factfulness by Hans Rosling, an outstanding international public health expert, is a hopeful book about the potential for human progress when we work off facts rather than our inherent biases." - Former U.S. President Barack Obama Factfulness: The stress-reducing habit of only carrying opinions for which you have strong supporting facts. When asked simple questions about global trends—what percentage of the world’s population live in poverty; why the world’s population is increasing; how many girls finish school—we systematically get the answers wrong. So wrong that a chimpanzee choosing answers at random will consistently outguess teachers, journalists, Nobel laureates, and investment bankers. In Factfulness, Professor of International Health and global TED phenomenon Hans Rosling, together with his two long-time collaborators, Anna and Ola, offers a radical new explanation of why this happens. They reveal the ten instincts that distort our perspective—from our tendency to divide the world into two camps (usually some version of us and them) to the way we consume media (where fear rules) to how we perceive progress (believing that most things are getting worse). Our problem is that we don’t know what we don’t know, and even our guesses are informed by unconscious and predictable biases. It turns out that the world, for all its imperfections, is in a much better state than we might think. That doesn’t mean there aren’t real concerns. But when we worry about everything all the time instead of embracing a worldview based on facts, we can lose our ability to focus on the things that threaten us most. Inspiring and revelatory, filled with lively anecdotes and moving stories, Factfulness is an urgent and essential book that will change the way you see the world and empower you to respond to the crises and opportunities of the future. --- “This book is my last battle in my life-long mission to fight devastating ignorance...Previously I armed myself with huge data sets, eye-opening software, an energetic learning style and a Swedish bayonet for sword-swallowing. It wasn’t enough. But I hope this book will be.” Hans Rosling, February 2017.
While challenging the teacher as hero trope, We Got This shows how authentically listening to kids is the closest thing to a superpower that we have. Cornelius identifies tools, attributes, and strategies that can augment our listening.
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
The how-to guide for exceptional management from the bottom up The Effective Manager is a hands-on practical guide to great management at every level. Written by the man behind Manager Tools, the world's number-one business podcast, this book distills the author's 25 years of management training expertise into clear, actionable steps to start taking today. First, you'll identify what "effective management" actually looks like: can you get the job done at a high level? Do you attract and retain top talent without burning them out? Then you'll dig into the four critical behaviors that make a manager great, and learn how to adjust your own behavior to be the leader your team needs. You'll learn the four major tools that should be a part of every manager's repertoire, how to use them, and even how to introduce them to the team in a productive, non-disruptive way. Most management books are written for CEOs and geared toward improving corporate management, but this book is expressly aimed at managers of any level—with a behavioral framework designed to be tailored to your team's specific needs. Understand your team's strengths, weaknesses, and goals in a meaningful way Stop limiting feedback to when something goes wrong Motivate your people to continuous improvement Spread the work around and let people stretch their skills Effective managers are good at the job and "good at people." The key is combining those skills to foster your team's development, get better and better results, and maintain a culture of positive productivity. The Effective Manager shows you how to turn good into great with clear, actionable, expert guidance.
Speaking out when it's unpopular. Back in the day, Henry David Thoreau raged at the robber barons-the big shots of their age, despoiling the environment in the name of progress. Deep in the throes of the seemingly unstoppable growth of tech, a modern-day Thoreau has emerged in the guise of Gerry McGovern-decrying the massive, hidden negative impacts of tech on the environment. McGovern has thoroughly documented in World Wide Waste how tech damages the Earth-and what we should be doing about it. It is not just the acres of discarded computer hardware conveniently dumped in Third World countries. Every time an email is downloaded it contributes to global warming. Every tweet, search, check of a webpage creates pollution. Digital is physical. Those data centers are not in the Cloud. They're on land in massive physical buildings packed full of computers hungry for energy. It seems invisible. It seems cheap and free. It's not. Digital costs the Earth.