Essentially, you make an initial guess, and then get more data to improve it. Bayes Theorem, or Bayes Rule, has a ton of real world applications, from estimating your risk of a heart attack to making recommendations on Netflix But It Isn't That Complicated This book is a short introduction to Bayes Theorem. It is only 15 pages long, and is intended to show you how Bayes Theorem works as quickly as possible. The examples are intentionally kept simple to focus solely on Bayes Theorem without requiring that the reader know complicated probability distributions. If you want to learn the basics of Bayes Theorem as quickly as possible, with some easy to duplicate examples, this is a good book for you.

    To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok.In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information (Alan Turing's role in breaking Germany's Enigma code during World War II), and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security.Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.

     Psychologists have long been aware that most people maintain an often irrationally positive outlook on life. In fact, optimism may be crucial to our existence. Tali Sharot’s experiments, research, and findings in cognitive science have contributed to an increased understanding of the biological basis of optimism. In this fascinating exploration, she takes an in-depth, clarifying look at how the brain generates hope and what happens when it fails; how the brains of optimists and pessimists differ; why we are terrible at predicting what will make us happy; how emotions strengthen our ability to recollect; how anticipation and dread affect us; and how our optimistic illusions affect our financial, professional, and emotional decisions.  With its cutting-edge science and its wide-ranging and accessible narrative, The Optimism Bias provides us with startling new insight into the workings of the brain.From the Hardcover edition.

    Scientists have long supported this assumption by claiming that emotions are hardwired in the body or the brain. Today, however, the science of emotion is in the midst of a revolution on par with the discovery of relativity in physics and natural selection in biology—ans this paradigm shift has far-reaching implications for us all.Leading the charge is psychologist and neuroscientist Lisa Feldman Barrett, whose theory of emotion is driving a deeper understanding of the mind and brain, and shedding new light on what it means to be human. Her research overturns the widely held belief that emotions are housed in different parts of the brain and are universally expressed and recognized. Instead, she has shown that emotion is constructed in the moment, by core systems that interact across the whole brain, aided by a lifetime of learning. This new theory means that you play a much greater role in your emotional life than you ever thought. Its repercussions are already shaking the foundations not only of psychology but also of medicine, the legal system, child-rearing, meditation, and even airport security.Why do emotions feel automatic? Does rational thought really control emotion? How does emotion affect disease? How can you make your children more emotionally intelligent? How Emotions Are Made answers these questions and many more, revealing the latest research and intriguing practical applications of the new science of emotion, mind, and brain.

    Some system of authority is a requirement of all communal living, and it is only the man dwelling in isolation who is not forced to respond, through defiance or submission, to the commands of others. Obedience, as a determinant of behavior is of particular relevance to our time. It has been reliably established that from 1933 to 1945 millions of innocent people were systematically slaughtered on command. Gas chambers were built, death camps were guarded, daily quotas of corpses were produced with the same efficiency as the manufacture of appliances. These inhumane policies may have originated in the mind of a single person, but they could only have been carried out on a massive scale if a very large number of people obeyed orders.Obedience is the psychological mechanism that links individual action to political purpose. It is the dispositional cement that binds men to systems of authority. Facts of recent history and observation in daily life suggest that for many people obedience may be a deeply ingrained behavior tendency, indeed, a prepotent impulse overriding training in ethics, sympathy, and moral conduct. C. P. Snow (1961) points to its importance when he writes:When you think of the long and gloomy history of man, you will find more hideous crimes have been committed in the name of obedience than have ever been committed in the name of rebellion. If you doubt that, read William Sbirer's 'Rise and Fall of the Third Reich.' The German Officer Corps were brought up in the most rigorous code of obedience . . . in the name of obedience they were party to, andassisted in, the most wicked large scale actions in the history of the world. (p. 24)The Nazi extermination of European Jews is the most extremeinstance of abhorrent immoral acts carried out by thousands ofpeople in the name of obedience. Yet in lesser degree this type ofthing is constantly recurring: ordinary citizens are ordered todestroy other people, and they do so because they consider ittheir duty to obey orders. Thus, obedience to authority, longpraised as a virtue, takes on a new aspect when it serves amalevolent cause; far from appearing as a virtue, it is transformedinto a heinous sin. Or is it?The moral question of whether one should obey when commands conflict with conscience was argued by Plato, dramatized in "Antigone," and treated to philosophic analysis in every historical epoch Conservative philosophers argue that the very fabric of society is threatened by disobedience, and even when the act prescribed by an authority is an evil one, it is better to carry out the act than to wrench at the structure of authority. Hobbes stated further that an act so executed is in no sense the responsibility of the person who carries it out but only of the authority that orders it. But humanists argue for the primacy of individual conscience in such matters, insisting that the moral judgments of the individual must override authority when the two are in conflict.The legal and philosophic aspects of obedience are of enormous import, but an empirically grounded scientist eventually comes to the point where he wishes to move from abstract discourse to the careful observation of concrete instances. In order to take a close look at the act of obeying, I set up a simple experimentat Yale University. Eventually, the experiment was to involve more than a thousand participants and would be repeated at several universities, but at the beginning, the conception was simple. A person comes to a psychological laboratory and is told to carry out a series of acts that come increasingly into conflict with conscience. The main question is how far the participant will comply with the experimenter's instructions before refusing to carry out the actions required of him.But the reader needs to know a little more detail about the experiment. Two people come to a psychology laboratory to take part in a study of memory and learning. One of them is designated as a "teacher" and the other a "learner." The experimenter explains that the study is concerned with the effects of punishment on learning. The learner is conducted into a room, seated in a chair, his arms strapped to prevent excessive movement, and an electrode attached to his wrist. He is told that he is to learn a list of word pairs; whenever he makes an error, be will receive electric shocks of increasing intensity.The real focus of the experiment is the teacher. After watching the learner being strapped into place, he is taken into the main experimental room and seated before an impressive shock generator. Its main feature is a horizontal line of thirty switches, ranging from 15 volts to 450 volts, in 15-volt increments. There are also verbal designations which range from Slight SHOCK to Danger--Severe SHOCK. The teacher is told that he is to administer the learning test to the man in the other room. When the learner responds correctly, the teacher moves on to the next item; when the other man gives an incorrectanswer, the teacher is to give him an electric shock. He is to start at the lowest shock level ( 15 volts) and to increase the level each time the man makes an error, going through 30 volts, 45 volts, and so on.The "teacher" is a genuinely naive subject who has come to the laboratory to participate in an experiment. The learner, or victim, is an actor who actually receives no shock at all. The point of the experiment is to see how far a person will proceed in a concrete and measurable situation in which he is ordered to inflict increasing pain on a protesting victim.

    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.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes. Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.

    But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.

    Cacioppo’s groundbreaking research topples one of the pillars of modern medicine and psychology: the focus on the individual as the unit of inquiry. By employing brain scans, monitoring blood pressure, and analyzing immune function, he demonstrates the overpowering influence of social context—a factor so strong that it can alter DNA replication. He defines an unrecognized syndrome—chronic loneliness—brings it out of the shadow of its cousin depression, and shows how this subjective sense of social isolation uniquely disrupts our perceptions, behavior, and physiology, becoming a trap that not only reinforces isolation but can also lead to early death. He gives the lie to the Hobbesian view of human nature as a “war of all against all,” and he shows how social cooperation is, in fact, humanity’s defining characteristic. Most important, he shows how we can break the trap of isolation for our benefit both as individuals and as a society.

    The controversial book linking intelligence to class and race in modern society, and what public policy can do to mitigate socioeconomic differences in IQ, birth rate, crime, fertility, welfare, and poverty.

    Mirroring his theory, Minsky boldly casts The Society of Mind as an intellectual puzzle whose pieces are assembled along the way. Each chapter -- on a self-contained page -- corresponds to a piece in the puzzle. As the pages turn, a unified theory of the mind emerges, like a mosaic. Ingenious, amusing, and easy to read, The Society of Mind is an adventure in imagination.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    Dozens of examples in innumeracy show us how it affects not only personal economics and travel plans, but explains mis-chosen mates, inappropriate drug-testing, and the allure of pseudo-science.