It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way.Data Visualization builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective "small multiple" plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible.Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings.Provides hands-on instruction using R and ggplot2Shows how the "tidyverse" of data analysis tools makes working with R easier and more consistentIncludes a library of data sets, code, and functions

    Their days are defined by a relentless barrage of incoming messages and back-and-forth digital conversations--a state of constant, anxious chatter in which nobody can disconnect, and so nobody has the cognitive bandwidth to perform substantive work. There was a time when tools like email felt cutting edge, but a thorough review of current evidence reveals that the hyperactive hive mind workflow they helped create has become a productivity disaster, reducing profitability and perhaps even slowing overall economic growth. Equally worrisome, it makes us miserable. Humans are simply not wired for constant digital communication.We have become so used to an inbox-driven workday that it's hard to imagine alternatives. But they do exist. Drawing on years of investigative reporting, author and computer science professor Cal Newport makes the case that our current approach to work is broken, then lays out a series of principles and concrete instructions for fixing it. In A World without Email, he argues for a workplace in which clear processes--not haphazard messaging--define how tasks are identified, assigned and reviewed. Each person works on fewer things (but does them better), and aggressive investment in support reduces the ever-increasing burden of administrative tasks. Above all else, important communication is streamlined, and inboxes and chat channels are no longer central to how work unfolds.The knowledge sector's evolution beyond the hyperactive hive mind is inevitable. The question is not whether a world without email is coming (it is), but whether you'll be ahead of this trend. If you're a CEO seeking a competitive edge, an entrepreneur convinced your productivity could be higher, or an employee exhausted by your inbox, A World Without Email will convince you that the time has come for bold changes, and will walk you through exactly how to make them happen.

    In this practical guide, data strategy consultant Max Shron shows you how to put the why before the how, through an often-overlooked set of analytical skills.Thinking with Data helps you learn techniques for turning data into knowledge you can use. You’ll learn a framework for defining your project, including the data you want to collect, and how you intend to approach, organize, and analyze the results. You’ll also learn patterns of reasoning that will help you unveil the real problem that needs to be solved.Learn a framework for scoping data projectsUnderstand how to pin down the details of an idea, receive feedback, and begin prototypingUse the tools of arguments to ask good questions, build projects in stages, and communicate resultsExplore data-specific patterns of reasoning and learn how to build more useful argumentsDelve into causal reasoning and learn how it permeates data workPut everything together, using extended examples to see the method of full problem thinking in action

    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 processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing 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.

    Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists--yes, even those published in peer-reviewed journals--are doing statistics wrong."Statistics Done Wrong" comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes.In this book, you'll learn: - Why "statistically significant" doesn't necessarily imply practical significance- Ideas behind hypothesis testing and regression analysis, and common misinterpretations of those ideas- How and how not to ask questions, design experiments, and work with data- Why many studies have too little data to detect what they're looking for-and, surprisingly, why this means published results are often overestimates- Why false positives are much more common than "significant at the 5% level" would suggestBy walking through colorful examples of statistics gone awry, the book offers approachable lessons on proper methodology, and each chapter ends with pro tips for practicing scientists and statisticians. No matter what your level of experience, "Statistics Done Wrong" will teach you how to be a better analyst, data scientist, or researcher.

    It's not for the faint of heart. It's for people who want to move mountains. It swallows some whole, but others derive endless invigoration and passion from the pace and the impact and the glory and the huge potential for failure as well as success. There's no other job like it, and this is a book to help you make it your job. The role of a product manager goes by many different names - and if that's not reason enough to be confused, some companies define product manager completely differently from how it's understood elsewhere. We sometimes get stuck in our quest to define the damn thing, but in the case of product management, it's effort well spent, because it's quite the jungle out there.

    "Looking to make a career change? Pivot is a book you will turn to again and again." —Daniel Pink, author of To Sell is Human and Drive Jenny Blake, author of Life After College and former career development program manager at Google, reveals how to methodically make your next career move by doubling down on what is already working.This book is for anyone searching for an answer to the question, "What's next?" Whether you have hit a plateau in your perfect-on-paper job, are considering taking on a new role in your current job, are thinking about starting your own business, or you want to move into a new industry altogether, one thing remains clear: your career success depends on your ability to determine your next best move.If change is the only constant, let’s get better at it.

    The findings will surprise many readers and, quite frankly, upset others.The ChallengeBuilt to Last, the defining management study of the nineties, showed how great companies triumph over time and how long-term sustained performance can be engineered into the DNA of an enterprise from the very beginning. But what about the company that is not born with great DNA? How can good companies, mediocre companies, even bad companies achieve enduring greatness? The StudyFor years, this question preyed on the mind of Jim Collins. Are there companies that defy gravity and convert long-term mediocrity or worse into long-term superiority? And if so, what are the universal distinguishing characteristics that cause a company to go from good to great?The StandardsUsing tough benchmarks, Collins and his research team identified a set of elite companies that made the leap to great results and sustained those results for at least fifteen years. How great? After the leap, the good-to-great companies generated cumulative stock returns that beat the general stock market by an average of seven times in fifteen years, better than twice the results delivered by a composite index of the world's greatest companies, including Coca-Cola, Intel, General Electric, and Merck. The ComparisonsThe research team contrasted the good-to-great companies with a carefully selected set of comparison companies that failed to make the leap from good to great. What was different? Why did one set of companies become truly great performers while the other set remained only good? The FindingsThe findings of the Good to Great study will surprise many readers and shed light on virtually every area of management strategy and practice. The findings include:Level 5 Leaders: The research team was shocked to discover the type of leadership required to achieve greatness.The Hedgehog Concept (Simplicity within the Three Circles): To go from good to great requires transcending the curse of competence.A Culture of Discipline: When you combine a culture of discipline with an ethic of entrepreneurship, you get the magical alchemy of great results. Technology Accelerators: Good-to-great companies think differently about the role of technology.The Flywheel and the Doom Loop: Those who launch radical change programs and wrenching restructurings will almost certainly fail to make the leap.

    Airbnb. Amazon. Apple. PayPal. All of these companies disrupted their markets when they launched. Today they are industry leaders. What’s the secret to their success?These cutting-edge businesses are built on platforms: two-sided markets that are revolutionizing the way we do business. Written by three of the most sought-after experts on platform businesses, Platform Revolution is the first authoritative, fact-based book on platform models. Whether platforms are connecting sellers and buyers, hosts and visitors, or drivers with people who need a ride, Geoffrey G. Parker, Marshall W. Van Alstyne, and Sangeet Paul Choudary reveal the what, how, and why of this revolution and provide the first “owner’s manual” for creating a successful platform business.Platform Revolution teaches newcomers how to start and run a successful platform business, explaining ways to identify prime markets and monetize networks. Addressing current business leaders, the authors reveal strategies behind some of today’s up-and-coming platforms, such as Tinder and SkillShare, and explain how traditional companies can adapt in a changing marketplace. The authors also cover essential issues concerning security, regulation, and consumer trust, while examining markets that may be ripe for a platform revolution, including healthcare, education, and energy.As digital networks increase in ubiquity, businesses that do a better job of harnessing the power of the platform will win. An indispensable guide, Platform Revolution charts out the brilliant future of platforms and reveals how they will irrevocably alter the lives and careers of millions.

    The tools and recipes in this book will help you uncover and solve hidden (and not-so-hidden) problems with your technology, your methodology, and those difficult "people" issues on your team.Project retrospectives help teams examine what went right and what went wrong on a project. But traditionally, retrospectives (also known as "post-mortems") are only helpful at the end of the project--too late to help. You need agile retrospectives that are iterative and incremental. You need to accurately find and fix problems to help the team today.Now, Derby and Larsen show you the tools, tricks, and tips you need to fix the problems you face on a software development project on an on-going basis. You'll see how to architect retrospectives in general, how to design them specifically for your team and organization, how to run them effectively, how to make the needed changes, and how to scale these techniques up. You'll learn how to deal with problems, and implement solutions effectively throughout the project--not just at the end.With regular tune-ups, your team will hum like a precise, world-class orchestra.ContentsForwardPrefaceIntroduction1. Helping your team inspect and adapt2. A retrospective custom-fit for your team3. Leading retrospectives4. Activities to set the stage5. Activities to gather data6. Activities to gather insights7. Activities to decide what to do8. Activities to close the retrospective9. Releases and project retrospectives10. Make it soA1. Facilitation suppliesA2. Debriefing activitiesA3. Activities quick reference matrixA4. Resources for learning facilitation skillsA5. Bibliography

    We're rebelling against technology that's too complicated, DVD players with too many menus, and software accompanied by 75-megabyte "read me" manuals. The iPod's clean gadgetry has made simplicity hip. But sometimes we find ourselves caught up in the simplicity paradox: we want something that's simple and easy to use, but also does all the complex things we might ever want it to do. In The Laws of Simplicity, John Maeda offers ten laws for balancing simplicity and complexity in business, technology, and design—guidelines for needing less and actually getting more.Maeda—a professor in MIT's Media Lab and a world-renowned graphic designer—explores the question of how we can redefine the notion of "improved" so that it doesn't always mean something more, something added on.Maeda's first law of simplicity is "Reduce." It's not necessarily beneficial to add technology features just because we can. And the features that we do have must be organized (Law 2) in a sensible hierarchy so users aren't distracted by features and functions they don't need. But simplicity is not less just for the sake of less. Skip ahead to Law 9: "Failure: Accept the fact that some things can never be made simple." Maeda's concise guide to simplicity in the digital age shows us how this idea can be a cornerstone of organizations and their products—how it can drive both business and technology. We can learn to simplify without sacrificing comfort and meaning, and we can achieve the balance described in Law 10. This law, which Maeda calls "The One," tells us: "Simplicity is about subtracting the obvious, and adding the meaningful."

    Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data.It's increasingly difficult to know what's true. Misinformation, disinformation, and fake news abound. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don't feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data.You don't need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit.We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism.

    As Senge makes clear, in the long run the only sustainable competitive advantage is your organization’s ability to learn faster than the competition. The leadership stories in the book demonstrate the many ways that the core ideas in The Fifth Discipline, many of which seemed radical when first published in 1990, have become deeply integrated into people’s ways of seeing the world and their managerial practices. In The Fifth Discipline, Senge describes how companies can rid themselves of the learning “disabilities” that threaten their productivity and success by adopting the strategies of learning organizations—ones in which new and expansive patterns of thinking are nurtured, collective aspiration is set free, and people are continually learning how to create results they truly desire. The updated and revised Currency edition of this business classic contains over one hundred pages of new material based on interviews with dozens of practitioners at companies like BP, Unilever, Intel, Ford, HP, Saudi Aramco, and organizations like Roca, Oxfam, and The World Bank. It features a new Foreword about the success Peter Senge has achieved with learning organizations since the book’s inception, as well as new chapters on Impetus (getting started), Strategies, Leaders’ New Work, Systems Citizens, and Frontiers for the Future. Mastering the disciplines Senge outlines in the book will:• Reignite the spark of genuine learning driven by people focused on what truly matters to them• Bridge teamwork into macro-creativity• Free you of confining assumptions and mindsets• Teach you to see the forest and the trees• End the struggle between work and personal time

    Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it--whether we realize it or not.Where do you send your child for the best education? Big Data. Which airline should you choose to ensure a timely arrival? Big Data. Who will you vote for in the next election? Big Data.The problem is, the more data we have, the more difficult it is to interpret it. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations.In Numbersense, expert statistician Kaiser Fung explains when you should accept the conclusions of the Big Data experts--and when you should say, Wait . . . what? He delves deeply into a wide range of topics, offering the answers to important questions, such as:How does the college ranking system really work?Can an obesity measure solve America's biggest healthcare crisis?Should you trust current unemployment data issued by the government?How do you improve your fantasy sports team?Should you worry about businesses that track your data?Don't take for granted statements made in the media, by our leaders, or even by your best friend. We're on information overload today, and there's a lot of bad information out there.Numbersense gives you the insight into how Big Data interpretation works--and how it too often doesn't work. You won't come away with the skills of a professional statistician. But you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up.Praise for NumbersenseNumbersense correctly puts the emphasis not on the size of big data, but on the analysis of it. Lots of fun stories, plenty of lessons learned--in short, a great way to acquire your own sense of numbers!Thomas H. Davenport, coauthor of Competing on Analytics and President's Distinguished Professor of IT and Management, Babson CollegeKaiser's accessible business book will blow your mind like no other. You'll be smarter, and you won't even realize it. Buy. It. Now.Avinash Kaushik, Digital Marketing Evangelist, Google, and author, Web Analytics 2.0Each story in Numbersense goes deep into what you have to think about before you trust the numbers. Kaiser Fung ably demonstrates that it takes skill and resourcefulness to make the numbers confess their meaning.John Sall, Executive Vice President, SAS InstituteKaiser Fung breaks the bad news--a ton more data is no panacea--but then has got your back, revealing the pitfalls of analysis with stimulating stories from the front lines of business, politics, health care, government, and education. The remedy isn't an advanced degree, nor is it common sense. You need Numbersense.Eric Siegel, founder, Predictive Analytics World, and author, Predictive AnalyticsI laughed my way through this superb-useful-fun book and learned and relearned a lot. Highly recommended! Tom Peters, author of In Search of Excellence

    Those cartoons eventually led to a popular blog-gapingvoid.com-and a reputation for pithy insight and humor, in both words and pictures.MacLeod has opinions on everything from marketing to the meaning of life, but one of his main subjects is creativity. How do new ideas emerge in a cynical, risk-averse world? Where does inspiration come from? What does it take to make a living as a creative person?Ignore Everybody expands on MacLeod's sharpest insights, wittiest cartoons, and most useful advice. For example:-Selling out is harder than it looks. Diluting your product to make it more commercial will just make people like it less.-If your plan depends on you suddenly being "discovered" by some big shot, your plan will probably fail. Nobody suddenly discovers anything. Things are made slowly and in pain.-Don't try to stand out from the crowd; avoid crowds altogether. There's no point trying to do the same thing as 250,000 other young hopefuls, waiting for a miracle. All existing business models are wrong. Find a new one.-The idea doesn't have to be big. It just has to be yours. The sovereignty you have over your work will inspire far more people than the actual content ever will.After learning MacLeod's forty keys to creativity, you will be ready to unlock your own brilliance and unleash it on the world.