Suppose that different food inspectors give different ratings to indistinguishable restaurants — or that when a company is handling customer complaints, the resolution depends on who happens to be handling the particular complaint. Now imagine that the same doctor, the same judge, the same inspector, or the same company official makes different decisions, depending on whether it is morning or afternoon, or Monday rather than Wednesday. These are examples of noise: variability in judgments that should be identical.   In Noise, Daniel Kahneman, Cass R. Sunstein, and Olivier Sibony show how noise contributes significantly to errors in all fields, including medicine, law, economic forecasting, police behavior, food safety, bail, security checks at airports, strategy, and personnel selection. And although noise can be found wherever people make judgments and decisions, individuals and organizations alike are commonly oblivious to the role of chance in their judgments and in their actions.   Drawing on the latest findings in psychology and behavioral economics, and the same kind of diligent, insightful research that made Thinking, Fast and Slow and Nudge groundbreaking New York Times bestsellers, Noise explains how and why humans are so susceptible to noise in judgment — and what we can do about it.

    We are bombarded with more information each day than our brains can process—especially in election season. It's raining bad data, half-truths, and even outright lies. New York Times bestselling author Daniel J. Levitin shows how to recognize misleading announcements, statistics, graphs, and written reports revealing the ways lying weasels can use them. It's becoming harder to separate the wheat from the digital chaff. How do we distinguish misinformation, pseudo-facts, distortions, and outright lies from reliable information? Levitin groups his field guide into two categories—statistical infomation and faulty arguments—ultimately showing how science is the bedrock of critical thinking. Infoliteracy means understanding that there are hierarchies of source quality and bias that variously distort our information feeds via every media channel, including social media. We may expect newspapers, bloggers, the government, and Wikipedia to be factually and logically correct, but they so often aren't. We need to think critically about the words and numbers we encounter if we want to be successful at work, at play, and in making the most of our lives. This means checking the plausibility and reasoning—not passively accepting information, repeating it, and making decisions based on it. Readers learn to avoid the extremes of passive gullibility and cynical rejection. Levitin's charming, entertaining, accessible guide can help anyone wake up to a whole lot of things that aren't so. And catch some lying weasels in their tracks!

    Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions.Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more.Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businesses Helps readers see how to shepherd predictive analytics projects through their companies Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more Covers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies.

    His goal was to help shift the focus in Japanese education from memorization to critical thinking, by adapting some of the techniques he had learned as an elite McKinsey consultant.He was amazed to discover that adults were hungry for his fun and easy guide to problem solving and decision making. The book became a surprise Japanese bestseller, with more than 370,000 in print after six months. Now American businesspeople can also use it to master some powerful skills.Watanabe uses sample scenarios to illustrate his techniques, which include logic trees and matrixes. A rock band figures out how to drive up concert attendance. An aspiring animator budgets for a new computer purchase. Students decide which high school they will attend.Illustrated with diagrams and quirky drawings, the book is simple enough for a middleschooler to understand but sophisticated enough for business leaders to apply to their most challenging problems.

    The other books in the series are The Black Swan, Antifragile,and The Bed of Procrustes.

    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.

    If the facts don't hang together on a latticework of theory, you don't have them in a usable form. You've got to have models in your head."- Charlie Munger, investor, vice chairman of Berkshire HathawayThe world's greatest problem-solvers, forecasters, and decision-makers all rely on a set of frameworks and shortcuts that help them cut through complexity and separate good ideas from bad ones. They're called mental models, and you can find them in dense textbooks on psychology, physics, economics, and more.Or, you can just read Super Thinking, a fun, illustrated guide to every mental model you could possibly need. How can mental models help you? Well, here are just a few examples... • If you've ever been overwhelmed by a to-do list that's grown too long, maybe you need the Eisenhower Decision Matrix to help you prioritize. • Use the 5 Whys model to better understand people's motivations or get to the root cause of a problem. • Before concluding that your colleague who messes up your projects is out to sabotage you, consider Hanlon's Razor for an alternative explanation. • Ever sat through a bad movie just because you paid a lot for the ticket? You might be falling prey to Sunk Cost Fallacy. • Set up Forcing Functions, like standing meeting or deadlines, to help grease the wheels for changes you want to occur.So, the next time you find yourself faced with a difficult decision or just trying to understand a complex situation, let Super Thinking upgrade your brain with mental models.Note: in the US the subtitle is The Big Book of Mental Models and outside it is Upgrade Your Reasoning and Make Better Decisions with Mental Models.

    The book is rich with historical detail and characters, as well as astonishing revelations about espionage carried out in recent times by the UK, US, and China. Using unique access to the National Security Agency, GCHQ, Chinese officials, and senior executives from some of the most powerful global technology companies, Gordon Corera has gathered compelling stories from heads of state, hackers and spies of all stripes.Cyberspies is a ground-breaking exploration of the new space in which the worlds of espionage, diplomacy, international business, science, and technology collide.

    In 2005, the U.S. Air Force boasted it would now fly, fight, and win in cyberspace, the "fifth domain" of warfare. This book takes stock, twenty years on: is cyber war really coming? Has war indeed entered the fifth domain? Cyber War Will Not Take Place cuts through the hype and takes a fresh look at cyber security. Thomas Rid argues that the focus on war and winning distracts from the real challenge of cyberspace: non-violent confrontation that may rival or even replace violence in surprising ways. The threat consists of three different vectors: espionage, sabotage, and subversion. The author traces the most significant hacks and attacks, exploring the full spectrum of case studies from the shadowy world of computer espionage and weaponised code. With a mix of technical detail and rigorous political analysis, the book explores some key questions: What are cyber weapons? How have they changed the meaning of violence? How likely and how dangerous is crowd-sourced subversive activity? Why has there never been a lethal cyber attack against a country's critical infrastructure? How serious is the threat of "pure" cyber espionage, of exfiltrating data without infiltrating humans first? And who is most vulnerable: which countries, industries, individuals?

    This book is focused on the details of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks. It is based in part on the authors blog posts, lecture materials, and tutorials. The author is one of the co-developers of the Johns Hopkins Specialization in Data Science the largest data science program in the world that has enrolled more than 1.76 million people. The book is useful as a companion to introductory courses in data science or data analysis. It is also a useful reference tool for people tasked with reading and critiquing data analyses. It is based on the authors popular open-source guides available through his Github account (https://github.com/jtleek). The paper is also available through Leanpub (https://leanpub.com/datastyle), if the book is purchased on that platform you are entitled to lifetime free updates.

    More and more leading businesses today use estimation questions in interviews to test applicants' abilities to think on their feet. Guesstimation enables anyone with basic math and science skills to estimate virtually anything--quickly--using plausible assumptions and elementary arithmetic.Lawrence Weinstein and John Adam present an eclectic array of estimation problems that range from devilishly simple to quite sophisticated and from serious real-world concerns to downright silly ones. How long would it take a running faucet to fill the inverted dome of the Capitol? What is the total length of all the pickles consumed in the US in one year? What are the relative merits of internal-combustion and electric cars, of coal and nuclear energy? The problems are marvelously diverse, yet the skills to solve them are the same. The authors show how easy it is to derive useful ballpark estimates by breaking complex problems into simpler, more manageable ones--and how there can be many paths to the right answer. The book is written in a question-and-answer format with lots of hints along the way. It includes a handy appendix summarizing the few formulas and basic science concepts needed, and its small size and French-fold design make it conveniently portable. Illustrated with humorous pen-and-ink sketches, Guesstimation will delight popular-math enthusiasts and is ideal for the classroom.

    A former rocket scientist reveals the habits, ideas, and strategies that will empower you to turn the seemingly impossible into the possible. Rocket science is often celebrated as the ultimate triumph of technology. But it's not. Rather, it's the apex of a certain thought process -- a way to imagine the unimaginable and solve the unsolvable. It's the same thought process that enabled Neil Armstrong to take his giant leap for mankind, that allows spacecraft to travel millions of miles through outer space and land on a precise spot, and that brings us closer to colonizing other planets. Fortunately, you don't have to be a rocket scientist to think like one. In this accessible and practical book, Ozan Varol reveals nine simple strategies from rocket science that you can use to make your own giant leaps in work and life -- whether it's landing your dream job, accelerating your business, learning a new skill, or creating the next breakthrough product. Today, thinking like a rocket scientist is a necessity. We all encounter complex and unfamiliar problems in our lives. Those who can tackle these problems -- without clear guidelines and with the clock ticking -- enjoy an extraordinary advantage. Think Like a Rocket Scientist will inspire you to take your own moonshot and enable you to achieve liftoff.

    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

    In 1967, they said the USSR would have one of the fastest-growing economies in the year 2000; in 2000, the USSR did not exist. In 1911, it was pronounced that there would be no more wars in Europe; we all know how that turned out. Face it, experts are about as accurate as dart-throwing monkeys. And yet every day we ask them to predict the future — everything from the weather to the likelihood of a catastrophic terrorist attack. Future Babble is the first book to examine this phenomenon, showing why our brains yearn for certainty about the future, why we are attracted to those who predict it confidently, and why it’s so easy for us to ignore the trail of outrageously wrong forecasts.In this fast-paced, example-packed, sometimes darkly hilarious book, journalist Dan Gardner shows how seminal research by UC Berkeley professor Philip Tetlock proved that pundits who are more famous are less accurate — and the average expert is no more accurate than a flipped coin. Gardner also draws on current research in cognitive psychology, political science, and behavioral economics to discover something quite reassuring: The future is always uncertain, but the end is not always near.

     It is easy to be overwhelmed by the amount of information we encounter each day. Whether at work, at school, or in our personal endeavors, there’s a deepening (and inescapable) need for people to work with and understand information. Information architecture is the way that we arrange the parts of something to make it understandable as a whole. When we make things for others to use, the architecture of information that we choose greatly affects our ability to deliver our intended message to our users. We all face messes made of information and people. I define the word “mess” the same way that most dictionaries do: “A situation where the interactions between people and information are confusing or full of difficulties.” — Who doesn’t bump up against messes made of information and people every day? This book provides a seven step process for making sense of any mess. Each chapter contains a set of lessons as well as workbook exercises architected to help you to work through your own mess.