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.

    As we dream with him, we are taken further and further into mathematical theory, where ideas eventually take flight, until everyone--from those who fumble over fractions to those who solve complex equations in their heads--winds up marveling at what numbers can do.Hans Magnus Enzensberger is a true polymath, the kind of superb intellectual who loves thinking and marshals all of his charm and wit to share his passions with the world. In The Number Devil, he brings together the surreal logic of Alice in Wonderland and the existential geometry of Flatland with the kind of math everyone would love, if only they had a number devil to teach them.

    What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us.In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

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

    This is the amazing story of how the "map problem" was solved.The problem posed in the letter came from a former student: What is the least possible number of colors needed to fill in any map (real or invented) so that neighboring counties are always colored differently? This deceptively simple question was of minimal interest to cartographers, who saw little need to limit how many colors they used. But the problem set off a frenzy among professional mathematicians and amateur problem solvers, among them Lewis Carroll, an astronomer, a botanist, an obsessive golfer, the Bishop of London, a man who set his watch only once a year, a California traffic cop, and a bridegroom who spent his honeymoon coloring maps. In their pursuit of the solution, mathematicians painted maps on doughnuts and horseshoes and played with patterned soccer balls and the great rhombicuboctahedron. It would be more than one hundred years (and countless colored maps) later before the result was finally established. Even then, difficult questions remained, and the intricate solution--which involved no fewer than 1,200 hours of computer time--was greeted with as much dismay as enthusiasm.Providing a clear and elegant explanation of the problem and the proof, Robin Wilson tells how a seemingly innocuous question baffled great minds and stimulated exciting mathematics with far-flung applications. This is the entertaining story of those who failed to prove, and those who ultimately did prove, that four colors do indeed suffice to color any map.

    Covering various the materials needed by students in engineering, science, and mathematics, this calculus text makes effective use of computing technology, graphics, and applications. It presents at least two technology projects in each chapter.

    A scathingly funny reinterpretation of the Ten Commandments from the larger, louder half of world-famous magic duo Penn and Teller reveals an atheist's experience in the world: from performing on the Vegas strip with Siegfried and Roy to children and fatherhood to his ongoing dialogue with proselytizers of the Christian Right and the joys of sex while scuba-diving, Penn has an outrageous sense of humor and a brilliantly entertaining opinion on, well, anything you care to think of.

    according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog "AI Weirdness." She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans--all to understand the technology that governs so much of our daily lives.We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI really, and how does it solve problems, understand humans, and even drive self-driving cars?Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't--like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"?In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt--and how they reflect the best and worst of humanity. You Look Like a Thing and I Love You is the perfect book for anyone curious about what the robots in our lives are thinking.

     Once one of Silicon Valley’s greatest success stories, Facebook has been under constant fire for the past five years, roiled by controversies and crises. It turns out that while the tech giant was connecting the world, they were also mishandling users’ data, spreading fake news, and amplifying dangerous, polarizing hate speech. The company, many said, had simply lost its way. But the truth is far more complex. Leadership decisions enabled, and then attempted to deflect attention from, the crises. Time after time, Facebook’s engineers were instructed to create tools that encouraged people to spend as much time on the platform as possible, even as those same tools boosted inflammatory rhetoric, conspiracy theories, and partisan filter bubbles. And while consumers and lawmakers focused their outrage on privacy breaches and misinformation, Facebook solidified its role as the world’s most voracious data-mining machine, posting record profits, and shoring up its dominance via aggressive lobbying efforts. Drawing on their unrivaled sources, Sheera Frenkel and Cecilia Kang take readers inside the complex court politics, alliances and rivalries within the company to shine a light on the fatal cracks in the architecture of the tech behemoth. Their explosive, exclusive reporting led them to a shocking conclusion: The missteps of the last five years were not an anomaly but an inevitability—this is how Facebook was built to perform. In a period of great upheaval, growth has remained the one constant under the leadership of Mark Zuckerberg and Sheryl Sandberg. Both have been held up as archetypes of uniquely 21st century executives—he the tech “boy genius” turned billionaire, she the ultimate woman in business, an inspiration to millions through her books and speeches. But sealed off in tight circles of advisers and hobbled by their own ambition and hubris, each has stood by as their technology is coopted by hate-mongers, criminals and corrupt political regimes across the globe, with devastating consequences. In An Ugly Truth, they are at last held accountable.

    In defiance of doomsayers, Johnson finds librarians more vital and necessary than ever, as they fuse the tools of the digital age with love for the written word and the enduring values of truth, service to all, and free speech. This Book Is Overdue! is a romp through the ranks of information professionals who organize our messy world and offer old-fashioned human help through the maze.

    Albert-László Barabási, the nation’s foremost expert in the new science of networks and author of Bursts, takes us on an intellectual adventure to prove that social networks, corporations, and living organisms are more similar than previously thought. Grasping a full understanding of network science will someday allow us to design blue-chip businesses, stop the outbreak of deadly diseases, and influence the exchange of ideas and information. Just as James Gleick and the Erdos–Rényi model brought the discovery of chaos theory to the general public, Linked tells the story of the true science of the future and of experiments in statistical mechanics on the internet, all vital parts of what would eventually be called the Barabási–Albert model.

    We’re told that learning is all self-discipline, that we must confine ourselves to designated study areas, turn off the music, and maintain a strict ritual if we want to ace that test, memorize that presentation, or nail that piano recital.   But what if almost everything we were told about learning is wrong? And what if there was a way to achieve more with less effort?   In How We Learn, award-winning science reporter Benedict Carey sifts through decades of education research and landmark studies to uncover the truth about how our brains absorb and retain information. What he discovers is that, from the moment we are born, we are all learning quickly, efficiently, and automatically; but in our zeal to systematize the process we have ignored valuable, naturally enjoyable learning tools like forgetting, sleeping, and daydreaming. Is a dedicated desk in a quiet room really the best way to study? Can altering your routine improve your recall? Are there times when distraction is good? Is repetition necessary? Carey’s search for answers to these questions yields a wealth of strategies that make learning more a part of our everyday lives—and less of a chore.   By road testing many of the counterintuitive techniques described in this book, Carey shows how we can flex the neural muscles that make deep learning possible. Along the way he reveals why teachers should give final exams on the first day of class, why it’s wise to interleave subjects and concepts when learning any new skill, and when it’s smarter to stay up late prepping for that presentation than to rise early for one last cram session. And if this requires some suspension of disbelief, that’s because the research defies what we’ve been told, throughout our lives, about how best to learn.   The brain is not like a muscle, at least not in any straightforward sense. It is something else altogether, sensitive to mood, to timing, to circadian rhythms, as well as to location and environment. It doesn’t take orders well, to put it mildly. If the brain is a learning machine, then it is an eccentric one. In How We Learn, Benedict Carey shows us how to exploit its quirks to our advantage.  Praise for How We Learn“This book is a revelation. I feel as if I’ve owned a brain for fifty-four years and only now discovered the operating manual.”—Mary Roach, bestselling author of Stiff and Gulp“A welcome rejoinder to the faddish notion that learning is all about the hours put in.” —The New York Times Book Review   “A valuable, entertaining tool for educators, students and parents.” —Shelf Awareness   “How We Learn is more than a new approach to learning; it is a guide to making the most out of life. Who wouldn’t be interested in that?” —Scientific American   “I know of no other source that pulls together so much of what we know about the science of memory and couples it with practical, practicable advice.”—Daniel T. Willingham, professor of psychology at the University of Virginia

    "No rock critic-living or dead, American or otherwise-has ever written about pop music with the evocative, hyperpoetic perfectitude of Rob Sheffield." So said Chuck Klosterman about Love is a Mix Tape, Sheffield's paean to a lost love via its soundtrack. Now, in Talking to Girls About Duran Duran, Sheffield shares the soundtrack to his eighties adolescence. When he turned 13 in 1980, Rob Sheffield had a lot to learn about women, love, music and himself, and in Talking to Girls About Duran Duran we get a glimpse into his transformation from pasty, geeky "hermit boy" into a young man with his first girlfriend, his first apartment, and a sense of the world. These were the years of MTV and John Hughes movies; the era of big dreams and bigger shoulder pads; and, like any all-American boy, this one was searching for true love and maybe a cooler haircut. It's all here: Inept flirtations. Dumb crushes. Deplorable fashion choices. Members Only jackets. Girls, every last one of whom seems to be madly in love with the bassist of Duran Duran. Sheffield's coming-of-age story is one that we all know, with a playlist that any child of the eighties or anyone who just loves music will sing along with. These songs-and Sheffield's writing-will remind readers of that first kiss, that first car, and the moments that shaped their lives.

    From the first lesson to the last, each chapter introduces games of increasing complexity and then teaches the game theoretical tools necessary to solve them. Inside, you will find: All the basics fully explained, including pure strategy Nash equilibrium, mixed strategy Nash equilibrium, the mixed strategy algorithm, how to calculate payoffs, strict dominance, weak dominance, iterated elimination of strictly dominated strategies, iterated elimination of weakly dominated strategies, and more! Dozens of games solved, including the prisoner's dilemma, stag hunt, matching pennies, zero sum games, battle of the sexes/Bach or Stravinsky, chicken/snowdrift, pure coordination, deadlock, and safety in numbers! Crystal clear, line-by-line calculations of every step, with more than 200 images so you don't miss a thing! Tons of applications: war, trade, game shows, and duopolistic competition. Quick, efficient, and to the point, Game Theory 101: The Basics is perfect for introductory game theory, intermediate microeconomics, and political science.

    Rather, this is a drop in the ocean, a paddle in the shallow end of sex history, but I hope you will get pleasantly wet nonetheless.The act of sex has not changed since people first worked out what went where, but the ways in which society dictates how sex is culturally understood and performed have varied significantly through the ages. Humans are the only creatures that stigmatise particular sexual practices, and sex remains a deeply divisive issue around the world. Attitudes will change and grow – hopefully for the better – but sex will never be free of stigma or shame unless we acknowledge where it has come from.